Remove all spaces in the end of lines#478

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Merged
TomFinley merged 3 commits into from
Jul 3, 2018
Merged

Remove all spaces in the end of lines #478

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be612a5
remove all spaces in the end of lines
Jul 2, 2018
fff1041
revert new word placement
Jul 3, 2018
8d72c37
Merge branch 'master' into ivanidze/robotom_pacification
Jul 3, 2018
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36 changes: 18 additions & 18 deletions src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs
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Expand Up@@ -271,10 +271,10 @@ public static NormalizeTransform Create(IHostEnvironment env, MinMaxArguments ar
/// <param name="name">Name of the output column.</param>
/// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
/// /// <param name="useCdf">Whether to use CDF as the output.</param>
public static NormalizeTransform CreateMeanVarNormalizer(IHostEnvironment env,
IDataView input,
string name,
string source=null,
public static NormalizeTransform CreateMeanVarNormalizer(IHostEnvironment env,
IDataView input,
string name,
string source = null,
bool useCdf = Defaults.MeanVarCdf)
{
var args = new MeanVarArguments()
Expand DownExpand Up@@ -313,10 +313,10 @@ public static NormalizeTransform Create(IHostEnvironment env, MeanVarArguments a
/// <param name="name">Name of the output column.</param>
/// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
/// /// <param name="useCdf">Whether to use CDF as the output.</param>
public static NormalizeTransform CreateLogMeanVarNormalizer(IHostEnvironment env,
IDataView input,
string name,
string source=null,
public static NormalizeTransform CreateLogMeanVarNormalizer(IHostEnvironment env,
IDataView input,
string name,
string source = null,
bool useCdf = Defaults.LogMeanVarCdf)
{
var args = new LogMeanVarArguments()
Expand DownExpand Up@@ -347,10 +347,10 @@ public static NormalizeTransform Create(IHostEnvironment env, LogMeanVarArgument
return func;
}

public static NormalizeTransform CreateBinningNormalizer(IHostEnvironment env,
IDataView input,
string name,
string source=null,
public static NormalizeTransform CreateBinningNormalizer(IHostEnvironment env,
IDataView input,
string name,
string source = null,
int numBins = Defaults.NumBins)
{
var args = new BinArguments()
Expand DownExpand Up@@ -381,12 +381,12 @@ public static NormalizeTransform Create(IHostEnvironment env, BinArguments args,
return func;
}

public static NormalizeTransform CreateSupervisedBinningNormalizer(IHostEnvironment env,
IDataView input,
string labelColumn,
string name,
string source = null,
int numBins = Defaults.NumBins,
public static NormalizeTransform CreateSupervisedBinningNormalizer(IHostEnvironment env,
IDataView input,
string labelColumn,
string name,
string source = null,
int numBins = Defaults.NumBins,
int minBinSize = Defaults.MinBinSize)
{
var args = new SupervisedBinArguments()
Expand Down
8 changes: 4 additions & 4 deletions src/Microsoft.ML.FastTree/FastTreeClassification.cs
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Expand Up@@ -338,10 +338,10 @@ public void AdjustTreeOutputs(IChannel ch, RegressionTree tree,

public static partial class FastTree
{
[TlcModule.EntryPoint(Name = "Trainers.FastTreeBinaryClassifier",
Desc = FastTreeBinaryClassificationTrainer.Summary,
Remarks = FastTreeBinaryClassificationTrainer.Remarks,
UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
[TlcModule.EntryPoint(Name = "Trainers.FastTreeBinaryClassifier",
Desc = FastTreeBinaryClassificationTrainer.Summary,
Remarks = FastTreeBinaryClassificationTrainer.Remarks,
UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
ShortName = FastTreeBinaryClassificationTrainer.ShortName)]
public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastTreeBinaryClassificationTrainer.Arguments input)
{
Expand Down
6 changes: 3 additions & 3 deletions src/Microsoft.ML.FastTree/FastTreeRanking.cs
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Expand Up@@ -1096,10 +1096,10 @@ public static FastTreeRankingPredictor Create(IHostEnvironment env, ModelLoadCon

public static partial class FastTree
{
[TlcModule.EntryPoint(Name = "Trainers.FastTreeRanker",
Desc = FastTreeRankingTrainer.Summary,
[TlcModule.EntryPoint(Name = "Trainers.FastTreeRanker",
Desc = FastTreeRankingTrainer.Summary,
Remarks = FastTreeRankingTrainer.Remarks,
UserName = FastTreeRankingTrainer.UserNameValue,
UserName = FastTreeRankingTrainer.UserNameValue,
ShortName = FastTreeRankingTrainer.ShortName)]
public static CommonOutputs.RankingOutput TrainRanking(IHostEnvironment env, FastTreeRankingTrainer.Arguments input)
{
Expand Down
6 changes: 3 additions & 3 deletions src/Microsoft.ML.FastTree/FastTreeRegression.cs
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Expand Up@@ -449,9 +449,9 @@ public static FastTreeRegressionPredictor Create(IHostEnvironment env, ModelLoad
public static partial class FastTree
{
[TlcModule.EntryPoint(Name = "Trainers.FastTreeRegressor",
Desc = FastTreeRegressionTrainer.Summary,
Remarks = FastTreeRegressionTrainer.Remarks,
UserName = FastTreeRegressionTrainer.UserNameValue,
Desc = FastTreeRegressionTrainer.Summary,
Remarks = FastTreeRegressionTrainer.Remarks,
UserName = FastTreeRegressionTrainer.UserNameValue,
ShortName = FastTreeRegressionTrainer.ShortName)]
public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastTreeRegressionTrainer.Arguments input)
{
Expand Down
6 changes: 3 additions & 3 deletions src/Microsoft.ML.FastTree/FastTreeTweedie.cs
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Expand Up@@ -463,9 +463,9 @@ protected override void Map(ref VBuffer<float> src, ref float dst)

public static partial class FastTree
{
[TlcModule.EntryPoint(Name = "Trainers.FastTreeTweedieRegressor",
Desc = FastTreeTweedieTrainer.Summary,
UserName = FastTreeTweedieTrainer.UserNameValue,
[TlcModule.EntryPoint(Name = "Trainers.FastTreeTweedieRegressor",
Desc = FastTreeTweedieTrainer.Summary,
UserName = FastTreeTweedieTrainer.UserNameValue,
ShortName = FastTreeTweedieTrainer.ShortName)]
public static CommonOutputs.RegressionOutput TrainTweedieRegression(IHostEnvironment env, FastTreeTweedieTrainer.Arguments input)
{
Expand Down
8 changes: 4 additions & 4 deletions src/Microsoft.ML.FastTree/RandomForestClassification.cs
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Expand Up@@ -208,10 +208,10 @@ protected override void GetGradientInOneQuery(int query, int threadIndex)

public static partial class FastForest
{
[TlcModule.EntryPoint(Name = "Trainers.FastForestBinaryClassifier",
Desc = FastForestClassification.Summary,
Remarks = FastForestClassification.Remarks,
UserName = FastForestClassification.UserNameValue,
[TlcModule.EntryPoint(Name = "Trainers.FastForestBinaryClassifier",
Desc = FastForestClassification.Summary,
Remarks = FastForestClassification.Remarks,
UserName = FastForestClassification.UserNameValue,
ShortName = FastForestClassification.ShortName)]
public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastForestClassification.Arguments input)
{
Expand Down
6 changes: 3 additions & 3 deletions src/Microsoft.ML.FastTree/RandomForestRegression.cs
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Expand Up@@ -280,10 +280,10 @@ public BasicImpl(Dataset trainData, Arguments args)

public static partial class FastForest
{
[TlcModule.EntryPoint(Name = "Trainers.FastForestRegressor",
Desc = FastForestRegression.Summary,
[TlcModule.EntryPoint(Name = "Trainers.FastForestRegressor",
Desc = FastForestRegression.Summary,
Remarks = FastForestRegression.Remarks,
UserName = FastForestRegression.LoadNameValue,
UserName = FastForestRegression.LoadNameValue,
ShortName = FastForestRegression.ShortName)]
public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastForestRegression.Arguments input)
{
Expand Down
4 changes: 2 additions & 2 deletions src/Microsoft.ML.KMeansClustering/KMeansPlusPlusTrainer.cs
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Expand Up@@ -233,10 +233,10 @@ private static int ComputeNumThreads(IHost host, int? argNumThreads)
return Math.Max(1, maxThreads);
}

[TlcModule.EntryPoint(Name = "Trainers.KMeansPlusPlusClusterer",
[TlcModule.EntryPoint(Name = "Trainers.KMeansPlusPlusClusterer",
Desc = Summary,
Remarks = Remarks,
UserName = UserNameValue,
UserName = UserNameValue,
ShortName = ShortName)]
public static CommonOutputs.ClusteringOutput TrainKMeans(IHostEnvironment env, Arguments input)
{
Expand Down
4 changes: 2 additions & 2 deletions src/Microsoft.ML.PCA/PcaTrainer.cs
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Expand Up@@ -284,10 +284,10 @@ private static void PostProcess(VBuffer<Float>[] y, Float[] sigma, Float[] z, in
}
}

[TlcModule.EntryPoint(Name = "Trainers.PcaAnomalyDetector",
[TlcModule.EntryPoint(Name = "Trainers.PcaAnomalyDetector",
Desc = "Train an PCA Anomaly model.",
Remarks = PcaPredictor.Remarks,
UserName = UserNameValue,
UserName = UserNameValue,
ShortName = ShortName)]
public static CommonOutputs.AnomalyDetectionOutput TrainPcaAnomaly(IHostEnvironment env, Arguments input)
{
Expand Down
8 changes: 3 additions & 5 deletions src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineTrainer.cs
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Expand Up@@ -11,9 +11,7 @@
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FactorizationMachine;
using Microsoft.ML.Runtime.Internal.CpuMath;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Model;
using Microsoft.ML.Runtime.Training;

[assembly: LoadableClass(FieldAwareFactorizationMachineTrainer.Summary, typeof(FieldAwareFactorizationMachineTrainer), typeof(FieldAwareFactorizationMachineTrainer.Arguments),
Expand DownExpand Up@@ -413,10 +411,10 @@ public override FieldAwareFactorizationMachinePredictor CreatePredictor()
return _pred;
}

[TlcModule.EntryPoint(Name = "Trainers.FieldAwareFactorizationMachineBinaryClassifier",
Desc = Summary,
[TlcModule.EntryPoint(Name = "Trainers.FieldAwareFactorizationMachineBinaryClassifier",
Desc = Summary,
Remarks = Remarks,
UserName = UserName,
UserName = UserName,
ShortName = ShortName)]
public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
{
Expand Down
8 changes: 4 additions & 4 deletions src/Microsoft.ML.StandardLearners/Standard/LinearClassificationTrainer.cs
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Expand Up@@ -189,7 +189,7 @@ public abstract class ArgumentsBase : LearnerInputBaseWithLabel
public int? MaxIterations;

[Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")]
[TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
[TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
public bool Shuffle = true;

[Argument(ArgumentType.AtMostOnce, HelpText = "Convergence check frequency (in terms of number of iterations). Set as negative or zero for not checking at all. If left blank, it defaults to check after every 'numThreads' iterations.", NullName = "<Auto>", ShortName = "checkFreq")]
Expand DownExpand Up@@ -1507,7 +1507,7 @@ public sealed class Arguments : LearnerInputBaseWithWeight
public Double InitLearningRate = 0.01;

[Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")]
[TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
[TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
public bool Shuffle = true;

[Argument(ArgumentType.AtMostOnce, HelpText = "Apply weight to the positive class, for imbalanced data", ShortName = "piw")]
Expand DownExpand Up@@ -1795,10 +1795,10 @@ public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironm
/// </summary>
public static partial class Sdca
{
[TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentBinaryClassifier",
[TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentBinaryClassifier",
Desc = "Train an SDCA binary model.",
Remarks = LinearClassificationTrainer.Remarks,
UserName = LinearClassificationTrainer.UserNameValue,
UserName = LinearClassificationTrainer.UserNameValue,
ShortName = LinearClassificationTrainer.LoadNameValue)]
public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, LinearClassificationTrainer.Arguments input)
{
Expand Down
6 changes: 3 additions & 3 deletions src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LogisticRegression.cs
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Expand Up@@ -386,10 +386,10 @@ public override ParameterMixingCalibratedPredictor CreatePredictor()
new PlattCalibrator(Host, -1, 0));
}

[TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionBinaryClassifier",
Desc = Summary,
[TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionBinaryClassifier",
Desc = Summary,
Remarks = Remarks,
UserName = UserNameValue,
UserName = UserNameValue,
ShortName = ShortName)]
public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
{
Expand Down
6 changes: 3 additions & 3 deletions ...Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs
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Expand Up@@ -961,10 +961,10 @@ public IRow GetStatsIRowOrNull(RoleMappedSchema schema)
/// </summary>
public partial class LogisticRegression
{
[TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionClassifier",
Desc = Summary,
[TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionClassifier",
Desc = Summary,
Remarks = MulticlassLogisticRegression.Remarks,
UserName = MulticlassLogisticRegression.UserNameValue,
UserName = MulticlassLogisticRegression.UserNameValue,
ShortName = MulticlassLogisticRegression.ShortName)]
public static CommonOutputs.MulticlassClassificationOutput TrainMultiClass(IHostEnvironment env, MulticlassLogisticRegression.Arguments input)
{
Expand Down
4 changes: 2 additions & 2 deletions src/Microsoft.ML.StandardLearners/Standard/MultiClass/MultiClassNaiveBayesTrainer.cs
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Expand Up@@ -130,8 +130,8 @@ public override MultiClassNaiveBayesPredictor CreatePredictor()
return _predictor;
}

[TlcModule.EntryPoint(Name = "Trainers.NaiveBayesClassifier",
Desc = "Train a MultiClassNaiveBayesTrainer.",
[TlcModule.EntryPoint(Name = "Trainers.NaiveBayesClassifier",
Desc = "Train a MultiClassNaiveBayesTrainer.",
UserName = UserName, ShortName = ShortName)]
public static CommonOutputs.MulticlassClassificationOutput TrainMultiClassNaiveBayesTrainer(IHostEnvironment env, Arguments input)
{
Expand Down
4 changes: 2 additions & 2 deletions src/Microsoft.ML.StandardLearners/Standard/Online/AveragedPerceptron.cs
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Expand Up@@ -110,10 +110,10 @@ public override LinearBinaryPredictor CreatePredictor()
return new LinearBinaryPredictor(Host, ref weights, bias);
}

[TlcModule.EntryPoint(Name = "Trainers.AveragedPerceptronBinaryClassifier",
[TlcModule.EntryPoint(Name = "Trainers.AveragedPerceptronBinaryClassifier",
Desc = Summary,
Remarks = Remarks,
UserName = UserNameValue,
UserName = UserNameValue,
ShortName = ShortName)]
public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
{
Expand Down
2 changes: 1 addition & 1 deletion src/Microsoft.ML.StandardLearners/Standard/Online/OnlineGradientDescent.cs
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Expand Up@@ -94,7 +94,7 @@ public override TPredictor CreatePredictor()
return new LinearRegressionPredictor(Host, ref weights, bias);
}

[TlcModule.EntryPoint(Name = "Trainers.OnlineGradientDescentRegressor",
[TlcModule.EntryPoint(Name = "Trainers.OnlineGradientDescentRegressor",
Desc = "Train a Online gradient descent perceptron.",
Remarks = Remarks,
UserName = UserNameValue,
Expand Down
2 changes: 1 addition & 1 deletion src/Microsoft.ML.StandardLearners/Standard/PoissonRegression/PoissonRegression.cs
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Expand Up@@ -32,7 +32,7 @@ public sealed class PoissonRegression : LbfgsTrainerBase<Float, PoissonRegressio
internal const string UserNameValue = "Poisson Regression";
internal const string ShortName = "PR";
internal const string Summary = "Poisson Regression assumes the unknown function, denoted Y has a Poisson distribution.";
new internal const string Remarks = @"<remarks>
internal new const string Remarks = @"<remarks>

@zeahmedzeahmedJul 3, 2018

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@Ivanidzo4ka, It has be reverted here as well...:)
I have opened PR (486) to fix it.

<a href='https://en.wikipedia.org/wiki/Poisson_regression'>Poisson regression</a> is a parameterized regression method.
It assumes that the log of the conditional mean of the dependent variable follows a linear function of the dependent variables.
Assuming that the dependent variable follows a Poisson distribution, the parameters of the regressor can be estimated by maximizing the likelihood of the obtained observations.
Expand Down
6 changes: 3 additions & 3 deletions src/Microsoft.ML.StandardLearners/Standard/SdcaMultiClass.cs
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Expand Up@@ -386,10 +386,10 @@ protected override Float GetInstanceWeight(FloatLabelCursor cursor)
/// </summary>
public static partial class Sdca
{
[TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentClassifier",
Desc = SdcaMultiClassTrainer.Summary,
[TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentClassifier",
Desc = SdcaMultiClassTrainer.Summary,
Remarks = SdcaMultiClassTrainer.Remarks,
UserName = SdcaMultiClassTrainer.UserNameValue,
UserName = SdcaMultiClassTrainer.UserNameValue,
ShortName = SdcaMultiClassTrainer.ShortName)]
public static CommonOutputs.MulticlassClassificationOutput TrainMultiClass(IHostEnvironment env, SdcaMultiClassTrainer.Arguments input)
{
Expand Down
4 changes: 2 additions & 2 deletions src/Microsoft.ML.StandardLearners/Standard/SdcaRegression.cs
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Expand Up@@ -131,10 +131,10 @@ protected override Float TuneDefaultL2(IChannel ch, int maxIterations, long rowC
/// </summary>
public static partial class Sdca
{
[TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentRegressor",
[TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentRegressor",
Desc = SdcaRegressionTrainer.Summary,
Remarks = SdcaRegressionTrainer.Remarks,
UserName = SdcaRegressionTrainer.UserNameValue,
UserName = SdcaRegressionTrainer.UserNameValue,
ShortName = SdcaRegressionTrainer.ShortName)]
public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, SdcaRegressionTrainer.Arguments input)
{
Expand Down
10 changes: 5 additions & 5 deletions src/Microsoft.ML.Transforms/BootstrapSampleTransform.cs
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Expand Up@@ -92,11 +92,11 @@ public BootstrapSampleTransform(IHostEnvironment env, Arguments args, IDataView
/// <param name="seed">The random seed. If unspecified random state will be instead derived from the environment.</param>
/// <param name="shuffleInput">Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.</param>
/// <param name="poolSize">When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.</param>
public BootstrapSampleTransform(IHostEnvironment env,
IDataView input,
bool complement = Defaults.Complement,
uint? seed = null,
bool shuffleInput = Defaults.ShuffleInput,
public BootstrapSampleTransform(IHostEnvironment env,
IDataView input,
bool complement = Defaults.Complement,
uint? seed = null,
bool shuffleInput = Defaults.ShuffleInput,
int poolSize = Defaults.PoolSize)
: this(env, new Arguments() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
{
Expand Down
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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
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Remove all spaces in the end of lines#478

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 Merged

TomFinley
merged 3 commits into

from

Jul 3, 2018
 Merged


Remove all spaces in the end of lines
#478
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be612a5

remove all spaces in the end of lines

Jul 2, 2018
fff1041

revert new word placement

Jul 3, 2018
8d72c37

Merge branch 'master' into ivanidze/robotom_pacification

Jul 3, 2018

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36 changes: 18 additions & 18 deletions
src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -271,10 +271,10 @@ public static NormalizeTransform Create(IHostEnvironment env, MinMaxArguments ar
 /// <param name="name">Name of the output column.</param>
 /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
 /// /// <param name="useCdf">Whether to use CDF as the output.</param>
 public static NormalizeTransform CreateMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 bool useCdf = Defaults.MeanVarCdf)
 {
 var args = new MeanVarArguments()
Expand DownExpand Up@@ -313,10 +313,10 @@ public static NormalizeTransform Create(IHostEnvironment env, MeanVarArguments a
 /// <param name="name">Name of the output column.</param>
 /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
 /// /// <param name="useCdf">Whether to use CDF as the output.</param>
 public static NormalizeTransform CreateLogMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateLogMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 bool useCdf = Defaults.LogMeanVarCdf)
 {
 var args = new LogMeanVarArguments()
Expand DownExpand Up@@ -347,10 +347,10 @@ public static NormalizeTransform Create(IHostEnvironment env, LogMeanVarArgument
 return func;
 }

 public static NormalizeTransform CreateBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 int numBins = Defaults.NumBins)
 {
 var args = new BinArguments()
Expand DownExpand Up@@ -381,12 +381,12 @@ public static NormalizeTransform Create(IHostEnvironment env, BinArguments args,
 return func;
 }

 public static NormalizeTransform CreateSupervisedBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string labelColumn,
 string name,
 string source = null,
 int numBins = Defaults.NumBins,
 public static NormalizeTransform CreateSupervisedBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string labelColumn,
 string name,
 string source = null,
 int numBins = Defaults.NumBins,
 int minBinSize = Defaults.MinBinSize)
 {
 var args = new SupervisedBinArguments()
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.FastTree/FastTreeClassification.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -338,10 +338,10 @@ public void AdjustTreeOutputs(IChannel ch, RegressionTree tree,

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeBinaryClassifier",
 Desc = FastTreeBinaryClassificationTrainer.Summary,
 Remarks = FastTreeBinaryClassificationTrainer.Remarks,
 UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeBinaryClassifier",
 Desc = FastTreeBinaryClassificationTrainer.Summary,
 Remarks = FastTreeBinaryClassificationTrainer.Remarks,
 UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
 ShortName = FastTreeBinaryClassificationTrainer.ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastTreeBinaryClassificationTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeRanking.cs

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Expand Up@@ -1096,10 +1096,10 @@ public static FastTreeRankingPredictor Create(IHostEnvironment env, ModelLoadCon

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRanker",
 Desc = FastTreeRankingTrainer.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRanker",
 Desc = FastTreeRankingTrainer.Summary,
 Remarks = FastTreeRankingTrainer.Remarks,
 UserName = FastTreeRankingTrainer.UserNameValue,
 UserName = FastTreeRankingTrainer.UserNameValue,
 ShortName = FastTreeRankingTrainer.ShortName)]
 public static CommonOutputs.RankingOutput TrainRanking(IHostEnvironment env, FastTreeRankingTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeRegression.cs

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Expand Up@@ -449,9 +449,9 @@ public static FastTreeRegressionPredictor Create(IHostEnvironment env, ModelLoad
 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRegressor",
 Desc = FastTreeRegressionTrainer.Summary,
 Remarks = FastTreeRegressionTrainer.Remarks,
 UserName = FastTreeRegressionTrainer.UserNameValue,
 Desc = FastTreeRegressionTrainer.Summary,
 Remarks = FastTreeRegressionTrainer.Remarks,
 UserName = FastTreeRegressionTrainer.UserNameValue,
 ShortName = FastTreeRegressionTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastTreeRegressionTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeTweedie.cs

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Expand Up@@ -463,9 +463,9 @@ protected override void Map(ref VBuffer<float> src, ref float dst)

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeTweedieRegressor",
 Desc = FastTreeTweedieTrainer.Summary,
 UserName = FastTreeTweedieTrainer.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeTweedieRegressor",
 Desc = FastTreeTweedieTrainer.Summary,
 UserName = FastTreeTweedieTrainer.UserNameValue,
 ShortName = FastTreeTweedieTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainTweedieRegression(IHostEnvironment env, FastTreeTweedieTrainer.Arguments input)
 {
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.FastTree/RandomForestClassification.cs

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Expand Up@@ -208,10 +208,10 @@ protected override void GetGradientInOneQuery(int query, int threadIndex)

 public static partial class FastForest
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastForestBinaryClassifier",
 Desc = FastForestClassification.Summary,
 Remarks = FastForestClassification.Remarks,
 UserName = FastForestClassification.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastForestBinaryClassifier",
 Desc = FastForestClassification.Summary,
 Remarks = FastForestClassification.Remarks,
 UserName = FastForestClassification.UserNameValue,
 ShortName = FastForestClassification.ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastForestClassification.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/RandomForestRegression.cs

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Expand Up@@ -280,10 +280,10 @@ public BasicImpl(Dataset trainData, Arguments args)

 public static partial class FastForest
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastForestRegressor",
 Desc = FastForestRegression.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FastForestRegressor",
 Desc = FastForestRegression.Summary,
 Remarks = FastForestRegression.Remarks,
 UserName = FastForestRegression.LoadNameValue,
 UserName = FastForestRegression.LoadNameValue,
 ShortName = FastForestRegression.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastForestRegression.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.KMeansClustering/KMeansPlusPlusTrainer.cs

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Expand Up@@ -233,10 +233,10 @@ private static int ComputeNumThreads(IHost host, int? argNumThreads)
 return Math.Max(1, maxThreads);
 }

 [TlcModule.EntryPoint(Name = "Trainers.KMeansPlusPlusClusterer",
 [TlcModule.EntryPoint(Name = "Trainers.KMeansPlusPlusClusterer",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.ClusteringOutput TrainKMeans(IHostEnvironment env, Arguments input)
 {
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4 changes: 2 additions & 2 deletions
src/Microsoft.ML.PCA/PcaTrainer.cs

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Expand Up@@ -284,10 +284,10 @@ private static void PostProcess(VBuffer<Float>[] y, Float[] sigma, Float[] z, in
 }
 }

 [TlcModule.EntryPoint(Name = "Trainers.PcaAnomalyDetector",
 [TlcModule.EntryPoint(Name = "Trainers.PcaAnomalyDetector",
 Desc = "Train an PCA Anomaly model.",
 Remarks = PcaPredictor.Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.AnomalyDetectionOutput TrainPcaAnomaly(IHostEnvironment env, Arguments input)
 {
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8 changes: 3 additions & 5 deletions
src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineTrainer.cs

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Expand Up@@ -11,9 +11,7 @@
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FactorizationMachine;
using Microsoft.ML.Runtime.Internal.CpuMath;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Model;
using Microsoft.ML.Runtime.Training;

[assembly: LoadableClass(FieldAwareFactorizationMachineTrainer.Summary, typeof(FieldAwareFactorizationMachineTrainer), typeof(FieldAwareFactorizationMachineTrainer.Arguments),
Expand DownExpand Up@@ -413,10 +411,10 @@ public override FieldAwareFactorizationMachinePredictor CreatePredictor()
 return _pred;
 }

 [TlcModule.EntryPoint(Name = "Trainers.FieldAwareFactorizationMachineBinaryClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FieldAwareFactorizationMachineBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserName,
 UserName = UserName,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.StandardLearners/Standard/LinearClassificationTrainer.cs

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Expand Up@@ -189,7 +189,7 @@ public abstract class ArgumentsBase : LearnerInputBaseWithLabel
 public int? MaxIterations;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 public bool Shuffle = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Convergence check frequency (in terms of number of iterations). Set as negative or zero for not checking at all. If left blank, it defaults to check after every 'numThreads' iterations.", NullName = "<Auto>", ShortName = "checkFreq")]
Expand DownExpand Up@@ -1507,7 +1507,7 @@ public sealed class Arguments : LearnerInputBaseWithWeight
 public Double InitLearningRate = 0.01;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 public bool Shuffle = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Apply weight to the positive class, for imbalanced data", ShortName = "piw")]
Expand DownExpand Up@@ -1795,10 +1795,10 @@ public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironm
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentBinaryClassifier",
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentBinaryClassifier",
 Desc = "Train an SDCA binary model.",
 Remarks = LinearClassificationTrainer.Remarks,
 UserName = LinearClassificationTrainer.UserNameValue,
 UserName = LinearClassificationTrainer.UserNameValue,
 ShortName = LinearClassificationTrainer.LoadNameValue)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, LinearClassificationTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LogisticRegression.cs

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Expand Up@@ -386,10 +386,10 @@ public override ParameterMixingCalibratedPredictor CreatePredictor()
 new PlattCalibrator(Host, -1, 0));
 }

 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionBinaryClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
...Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs

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Expand Up@@ -961,10 +961,10 @@ public IRow GetStatsIRowOrNull(RoleMappedSchema schema)
 /// </summary>
 public partial class LogisticRegression
 {
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionClassifier",
 Desc = Summary,
 Remarks = MulticlassLogisticRegression.Remarks,
 UserName = MulticlassLogisticRegression.UserNameValue,
 UserName = MulticlassLogisticRegression.UserNameValue,
 ShortName = MulticlassLogisticRegression.ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClass(IHostEnvironment env, MulticlassLogisticRegression.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/MultiClass/MultiClassNaiveBayesTrainer.cs

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Expand Up@@ -130,8 +130,8 @@ public override MultiClassNaiveBayesPredictor CreatePredictor()
 return _predictor;
 }

 [TlcModule.EntryPoint(Name = "Trainers.NaiveBayesClassifier",
 Desc = "Train a MultiClassNaiveBayesTrainer.",
 [TlcModule.EntryPoint(Name = "Trainers.NaiveBayesClassifier",
 Desc = "Train a MultiClassNaiveBayesTrainer.",
 UserName = UserName, ShortName = ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClassNaiveBayesTrainer(IHostEnvironment env, Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/Online/AveragedPerceptron.cs

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Expand Up@@ -110,10 +110,10 @@ public override LinearBinaryPredictor CreatePredictor()
 return new LinearBinaryPredictor(Host, ref weights, bias);
 }

 [TlcModule.EntryPoint(Name = "Trainers.AveragedPerceptronBinaryClassifier",
 [TlcModule.EntryPoint(Name = "Trainers.AveragedPerceptronBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.StandardLearners/Standard/Online/OnlineGradientDescent.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -94,7 +94,7 @@ public override TPredictor CreatePredictor()
 return new LinearRegressionPredictor(Host, ref weights, bias);
 }

 [TlcModule.EntryPoint(Name = "Trainers.OnlineGradientDescentRegressor",
 [TlcModule.EntryPoint(Name = "Trainers.OnlineGradientDescentRegressor",
 Desc = "Train a Online gradient descent perceptron.",
 Remarks = Remarks,
 UserName = UserNameValue,
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.StandardLearners/Standard/PoissonRegression/PoissonRegression.cs

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Expand Up@@ -32,7 +32,7 @@ public sealed class PoissonRegression : LbfgsTrainerBase<Float, PoissonRegressio
 internal const string UserNameValue = "Poisson Regression";
 internal const string ShortName = "PR";
 internal const string Summary = "Poisson Regression assumes the unknown function, denoted Y has a Poisson distribution.";
new internal const string Remarks = @"<remarks>
 internal new const string Remarks = @"<remarks>
@zeahmedzeahmedJul 3, 2018

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@Ivanidzo4ka, It has be reverted here as well...:)

I have opened PR (486) to fix it.
<a href='https://en.wikipedia.org/wiki/Poisson_regression'>Poisson regression</a> is a parameterized regression method. 
It assumes that the log of the conditional mean of the dependent variable follows a linear function of the dependent variables. 
Assuming that the dependent variable follows a Poisson distribution, the parameters of the regressor can be estimated by maximizing the likelihood of the obtained observations.
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.StandardLearners/Standard/SdcaMultiClass.cs

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Expand Up@@ -386,10 +386,10 @@ protected override Float GetInstanceWeight(FloatLabelCursor cursor)
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentClassifier",
 Desc = SdcaMultiClassTrainer.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentClassifier",
 Desc = SdcaMultiClassTrainer.Summary,
 Remarks = SdcaMultiClassTrainer.Remarks,
 UserName = SdcaMultiClassTrainer.UserNameValue,
 UserName = SdcaMultiClassTrainer.UserNameValue,
 ShortName = SdcaMultiClassTrainer.ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClass(IHostEnvironment env, SdcaMultiClassTrainer.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/SdcaRegression.cs

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Expand Up@@ -131,10 +131,10 @@ protected override Float TuneDefaultL2(IChannel ch, int maxIterations, long rowC
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentRegressor",
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentRegressor",
 Desc = SdcaRegressionTrainer.Summary,
 Remarks = SdcaRegressionTrainer.Remarks,
 UserName = SdcaRegressionTrainer.UserNameValue,
 UserName = SdcaRegressionTrainer.UserNameValue,
 ShortName = SdcaRegressionTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, SdcaRegressionTrainer.Arguments input)
 {
Expand Down

10 changes: 5 additions & 5 deletions
src/Microsoft.ML.Transforms/BootstrapSampleTransform.cs

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Expand Up@@ -92,11 +92,11 @@ public BootstrapSampleTransform(IHostEnvironment env, Arguments args, IDataView
 /// <param name="seed">The random seed. If unspecified random state will be instead derived from the environment.</param>
 /// <param name="shuffleInput">Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.</param>
 /// <param name="poolSize">When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.</param>
 public BootstrapSampleTransform(IHostEnvironment env,
 IDataView input,
 bool complement = Defaults.Complement,
 uint? seed = null,
 bool shuffleInput = Defaults.ShuffleInput,
 public BootstrapSampleTransform(IHostEnvironment env,
 IDataView input,
 bool complement = Defaults.Complement,
 uint? seed = null,
 bool shuffleInput = Defaults.ShuffleInput,
 int poolSize = Defaults.PoolSize)
 : this(env, new Arguments() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
 {
Expand Down
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if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
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var __re = new RegExp('^' + ".*" + '

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 Merged

TomFinley
merged 3 commits into

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Jul 3, 2018
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Remove all spaces in the end of lines
#478
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be612a5

remove all spaces in the end of lines

Jul 2, 2018
fff1041

revert new word placement

Jul 3, 2018
8d72c37

Merge branch 'master' into ivanidze/robotom_pacification

Jul 3, 2018

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36 changes: 18 additions & 18 deletions
src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs

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Expand Up@@ -271,10 +271,10 @@ public static NormalizeTransform Create(IHostEnvironment env, MinMaxArguments ar
 /// <param name="name">Name of the output column.</param>
 /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
 /// /// <param name="useCdf">Whether to use CDF as the output.</param>
 public static NormalizeTransform CreateMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 bool useCdf = Defaults.MeanVarCdf)
 {
 var args = new MeanVarArguments()
Expand DownExpand Up@@ -313,10 +313,10 @@ public static NormalizeTransform Create(IHostEnvironment env, MeanVarArguments a
 /// <param name="name">Name of the output column.</param>
 /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
 /// /// <param name="useCdf">Whether to use CDF as the output.</param>
 public static NormalizeTransform CreateLogMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateLogMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 bool useCdf = Defaults.LogMeanVarCdf)
 {
 var args = new LogMeanVarArguments()
Expand DownExpand Up@@ -347,10 +347,10 @@ public static NormalizeTransform Create(IHostEnvironment env, LogMeanVarArgument
 return func;
 }

 public static NormalizeTransform CreateBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 int numBins = Defaults.NumBins)
 {
 var args = new BinArguments()
Expand DownExpand Up@@ -381,12 +381,12 @@ public static NormalizeTransform Create(IHostEnvironment env, BinArguments args,
 return func;
 }

 public static NormalizeTransform CreateSupervisedBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string labelColumn,
 string name,
 string source = null,
 int numBins = Defaults.NumBins,
 public static NormalizeTransform CreateSupervisedBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string labelColumn,
 string name,
 string source = null,
 int numBins = Defaults.NumBins,
 int minBinSize = Defaults.MinBinSize)
 {
 var args = new SupervisedBinArguments()
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.FastTree/FastTreeClassification.cs

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Expand Up@@ -338,10 +338,10 @@ public void AdjustTreeOutputs(IChannel ch, RegressionTree tree,

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeBinaryClassifier",
 Desc = FastTreeBinaryClassificationTrainer.Summary,
 Remarks = FastTreeBinaryClassificationTrainer.Remarks,
 UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeBinaryClassifier",
 Desc = FastTreeBinaryClassificationTrainer.Summary,
 Remarks = FastTreeBinaryClassificationTrainer.Remarks,
 UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
 ShortName = FastTreeBinaryClassificationTrainer.ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastTreeBinaryClassificationTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeRanking.cs

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Expand Up@@ -1096,10 +1096,10 @@ public static FastTreeRankingPredictor Create(IHostEnvironment env, ModelLoadCon

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRanker",
 Desc = FastTreeRankingTrainer.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRanker",
 Desc = FastTreeRankingTrainer.Summary,
 Remarks = FastTreeRankingTrainer.Remarks,
 UserName = FastTreeRankingTrainer.UserNameValue,
 UserName = FastTreeRankingTrainer.UserNameValue,
 ShortName = FastTreeRankingTrainer.ShortName)]
 public static CommonOutputs.RankingOutput TrainRanking(IHostEnvironment env, FastTreeRankingTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeRegression.cs

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Expand Up@@ -449,9 +449,9 @@ public static FastTreeRegressionPredictor Create(IHostEnvironment env, ModelLoad
 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRegressor",
 Desc = FastTreeRegressionTrainer.Summary,
 Remarks = FastTreeRegressionTrainer.Remarks,
 UserName = FastTreeRegressionTrainer.UserNameValue,
 Desc = FastTreeRegressionTrainer.Summary,
 Remarks = FastTreeRegressionTrainer.Remarks,
 UserName = FastTreeRegressionTrainer.UserNameValue,
 ShortName = FastTreeRegressionTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastTreeRegressionTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeTweedie.cs

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Expand Up@@ -463,9 +463,9 @@ protected override void Map(ref VBuffer<float> src, ref float dst)

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeTweedieRegressor",
 Desc = FastTreeTweedieTrainer.Summary,
 UserName = FastTreeTweedieTrainer.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeTweedieRegressor",
 Desc = FastTreeTweedieTrainer.Summary,
 UserName = FastTreeTweedieTrainer.UserNameValue,
 ShortName = FastTreeTweedieTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainTweedieRegression(IHostEnvironment env, FastTreeTweedieTrainer.Arguments input)
 {
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.FastTree/RandomForestClassification.cs

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Expand Up@@ -208,10 +208,10 @@ protected override void GetGradientInOneQuery(int query, int threadIndex)

 public static partial class FastForest
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastForestBinaryClassifier",
 Desc = FastForestClassification.Summary,
 Remarks = FastForestClassification.Remarks,
 UserName = FastForestClassification.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastForestBinaryClassifier",
 Desc = FastForestClassification.Summary,
 Remarks = FastForestClassification.Remarks,
 UserName = FastForestClassification.UserNameValue,
 ShortName = FastForestClassification.ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastForestClassification.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/RandomForestRegression.cs

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Expand Up@@ -280,10 +280,10 @@ public BasicImpl(Dataset trainData, Arguments args)

 public static partial class FastForest
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastForestRegressor",
 Desc = FastForestRegression.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FastForestRegressor",
 Desc = FastForestRegression.Summary,
 Remarks = FastForestRegression.Remarks,
 UserName = FastForestRegression.LoadNameValue,
 UserName = FastForestRegression.LoadNameValue,
 ShortName = FastForestRegression.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastForestRegression.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.KMeansClustering/KMeansPlusPlusTrainer.cs

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Expand Up@@ -233,10 +233,10 @@ private static int ComputeNumThreads(IHost host, int? argNumThreads)
 return Math.Max(1, maxThreads);
 }

 [TlcModule.EntryPoint(Name = "Trainers.KMeansPlusPlusClusterer",
 [TlcModule.EntryPoint(Name = "Trainers.KMeansPlusPlusClusterer",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.ClusteringOutput TrainKMeans(IHostEnvironment env, Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.PCA/PcaTrainer.cs

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Expand Up@@ -284,10 +284,10 @@ private static void PostProcess(VBuffer<Float>[] y, Float[] sigma, Float[] z, in
 }
 }

 [TlcModule.EntryPoint(Name = "Trainers.PcaAnomalyDetector",
 [TlcModule.EntryPoint(Name = "Trainers.PcaAnomalyDetector",
 Desc = "Train an PCA Anomaly model.",
 Remarks = PcaPredictor.Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.AnomalyDetectionOutput TrainPcaAnomaly(IHostEnvironment env, Arguments input)
 {
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8 changes: 3 additions & 5 deletions
src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineTrainer.cs

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Expand Up@@ -11,9 +11,7 @@
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FactorizationMachine;
using Microsoft.ML.Runtime.Internal.CpuMath;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Model;
using Microsoft.ML.Runtime.Training;

[assembly: LoadableClass(FieldAwareFactorizationMachineTrainer.Summary, typeof(FieldAwareFactorizationMachineTrainer), typeof(FieldAwareFactorizationMachineTrainer.Arguments),
Expand DownExpand Up@@ -413,10 +411,10 @@ public override FieldAwareFactorizationMachinePredictor CreatePredictor()
 return _pred;
 }

 [TlcModule.EntryPoint(Name = "Trainers.FieldAwareFactorizationMachineBinaryClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FieldAwareFactorizationMachineBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserName,
 UserName = UserName,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
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8 changes: 4 additions & 4 deletions
src/Microsoft.ML.StandardLearners/Standard/LinearClassificationTrainer.cs

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Expand Up@@ -189,7 +189,7 @@ public abstract class ArgumentsBase : LearnerInputBaseWithLabel
 public int? MaxIterations;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 public bool Shuffle = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Convergence check frequency (in terms of number of iterations). Set as negative or zero for not checking at all. If left blank, it defaults to check after every 'numThreads' iterations.", NullName = "<Auto>", ShortName = "checkFreq")]
Expand DownExpand Up@@ -1507,7 +1507,7 @@ public sealed class Arguments : LearnerInputBaseWithWeight
 public Double InitLearningRate = 0.01;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 public bool Shuffle = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Apply weight to the positive class, for imbalanced data", ShortName = "piw")]
Expand DownExpand Up@@ -1795,10 +1795,10 @@ public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironm
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentBinaryClassifier",
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentBinaryClassifier",
 Desc = "Train an SDCA binary model.",
 Remarks = LinearClassificationTrainer.Remarks,
 UserName = LinearClassificationTrainer.UserNameValue,
 UserName = LinearClassificationTrainer.UserNameValue,
 ShortName = LinearClassificationTrainer.LoadNameValue)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, LinearClassificationTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LogisticRegression.cs

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Expand Up@@ -386,10 +386,10 @@ public override ParameterMixingCalibratedPredictor CreatePredictor()
 new PlattCalibrator(Host, -1, 0));
 }

 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionBinaryClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
...Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs

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Expand Up@@ -961,10 +961,10 @@ public IRow GetStatsIRowOrNull(RoleMappedSchema schema)
 /// </summary>
 public partial class LogisticRegression
 {
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionClassifier",
 Desc = Summary,
 Remarks = MulticlassLogisticRegression.Remarks,
 UserName = MulticlassLogisticRegression.UserNameValue,
 UserName = MulticlassLogisticRegression.UserNameValue,
 ShortName = MulticlassLogisticRegression.ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClass(IHostEnvironment env, MulticlassLogisticRegression.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/MultiClass/MultiClassNaiveBayesTrainer.cs

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Expand Up@@ -130,8 +130,8 @@ public override MultiClassNaiveBayesPredictor CreatePredictor()
 return _predictor;
 }

 [TlcModule.EntryPoint(Name = "Trainers.NaiveBayesClassifier",
 Desc = "Train a MultiClassNaiveBayesTrainer.",
 [TlcModule.EntryPoint(Name = "Trainers.NaiveBayesClassifier",
 Desc = "Train a MultiClassNaiveBayesTrainer.",
 UserName = UserName, ShortName = ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClassNaiveBayesTrainer(IHostEnvironment env, Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/Online/AveragedPerceptron.cs

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Expand Up@@ -110,10 +110,10 @@ public override LinearBinaryPredictor CreatePredictor()
 return new LinearBinaryPredictor(Host, ref weights, bias);
 }

 [TlcModule.EntryPoint(Name = "Trainers.AveragedPerceptronBinaryClassifier",
 [TlcModule.EntryPoint(Name = "Trainers.AveragedPerceptronBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.StandardLearners/Standard/Online/OnlineGradientDescent.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -94,7 +94,7 @@ public override TPredictor CreatePredictor()
 return new LinearRegressionPredictor(Host, ref weights, bias);
 }

 [TlcModule.EntryPoint(Name = "Trainers.OnlineGradientDescentRegressor",
 [TlcModule.EntryPoint(Name = "Trainers.OnlineGradientDescentRegressor",
 Desc = "Train a Online gradient descent perceptron.",
 Remarks = Remarks,
 UserName = UserNameValue,
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.StandardLearners/Standard/PoissonRegression/PoissonRegression.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -32,7 +32,7 @@ public sealed class PoissonRegression : LbfgsTrainerBase<Float, PoissonRegressio
 internal const string UserNameValue = "Poisson Regression";
 internal const string ShortName = "PR";
 internal const string Summary = "Poisson Regression assumes the unknown function, denoted Y has a Poisson distribution.";
new internal const string Remarks = @"<remarks>
 internal new const string Remarks = @"<remarks>
@zeahmedzeahmedJul 3, 2018

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@Ivanidzo4ka, It has be reverted here as well...:)

I have opened PR (486) to fix it.
<a href='https://en.wikipedia.org/wiki/Poisson_regression'>Poisson regression</a> is a parameterized regression method. 
It assumes that the log of the conditional mean of the dependent variable follows a linear function of the dependent variables. 
Assuming that the dependent variable follows a Poisson distribution, the parameters of the regressor can be estimated by maximizing the likelihood of the obtained observations.
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.StandardLearners/Standard/SdcaMultiClass.cs

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Expand Up@@ -386,10 +386,10 @@ protected override Float GetInstanceWeight(FloatLabelCursor cursor)
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentClassifier",
 Desc = SdcaMultiClassTrainer.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentClassifier",
 Desc = SdcaMultiClassTrainer.Summary,
 Remarks = SdcaMultiClassTrainer.Remarks,
 UserName = SdcaMultiClassTrainer.UserNameValue,
 UserName = SdcaMultiClassTrainer.UserNameValue,
 ShortName = SdcaMultiClassTrainer.ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClass(IHostEnvironment env, SdcaMultiClassTrainer.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/SdcaRegression.cs

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Expand Up@@ -131,10 +131,10 @@ protected override Float TuneDefaultL2(IChannel ch, int maxIterations, long rowC
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentRegressor",
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentRegressor",
 Desc = SdcaRegressionTrainer.Summary,
 Remarks = SdcaRegressionTrainer.Remarks,
 UserName = SdcaRegressionTrainer.UserNameValue,
 UserName = SdcaRegressionTrainer.UserNameValue,
 ShortName = SdcaRegressionTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, SdcaRegressionTrainer.Arguments input)
 {
Expand Down

10 changes: 5 additions & 5 deletions
src/Microsoft.ML.Transforms/BootstrapSampleTransform.cs

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Expand Up@@ -92,11 +92,11 @@ public BootstrapSampleTransform(IHostEnvironment env, Arguments args, IDataView
 /// <param name="seed">The random seed. If unspecified random state will be instead derived from the environment.</param>
 /// <param name="shuffleInput">Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.</param>
 /// <param name="poolSize">When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.</param>
 public BootstrapSampleTransform(IHostEnvironment env,
 IDataView input,
 bool complement = Defaults.Complement,
 uint? seed = null,
 bool shuffleInput = Defaults.ShuffleInput,
 public BootstrapSampleTransform(IHostEnvironment env,
 IDataView input,
 bool complement = Defaults.Complement,
 uint? seed = null,
 bool shuffleInput = Defaults.ShuffleInput,
 int poolSize = Defaults.PoolSize)
 : this(env, new Arguments() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
 {
Expand Down
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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 Merged

TomFinley
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Jul 3, 2018
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Remove all spaces in the end of lines
#478
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be612a5

remove all spaces in the end of lines

Jul 2, 2018
fff1041

revert new word placement

Jul 3, 2018
8d72c37

Merge branch 'master' into ivanidze/robotom_pacification

Jul 3, 2018

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36 changes: 18 additions & 18 deletions
src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs

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Expand Up@@ -271,10 +271,10 @@ public static NormalizeTransform Create(IHostEnvironment env, MinMaxArguments ar
 /// <param name="name">Name of the output column.</param>
 /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
 /// /// <param name="useCdf">Whether to use CDF as the output.</param>
 public static NormalizeTransform CreateMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 bool useCdf = Defaults.MeanVarCdf)
 {
 var args = new MeanVarArguments()
Expand DownExpand Up@@ -313,10 +313,10 @@ public static NormalizeTransform Create(IHostEnvironment env, MeanVarArguments a
 /// <param name="name">Name of the output column.</param>
 /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
 /// /// <param name="useCdf">Whether to use CDF as the output.</param>
 public static NormalizeTransform CreateLogMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateLogMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 bool useCdf = Defaults.LogMeanVarCdf)
 {
 var args = new LogMeanVarArguments()
Expand DownExpand Up@@ -347,10 +347,10 @@ public static NormalizeTransform Create(IHostEnvironment env, LogMeanVarArgument
 return func;
 }

 public static NormalizeTransform CreateBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 int numBins = Defaults.NumBins)
 {
 var args = new BinArguments()
Expand DownExpand Up@@ -381,12 +381,12 @@ public static NormalizeTransform Create(IHostEnvironment env, BinArguments args,
 return func;
 }

 public static NormalizeTransform CreateSupervisedBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string labelColumn,
 string name,
 string source = null,
 int numBins = Defaults.NumBins,
 public static NormalizeTransform CreateSupervisedBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string labelColumn,
 string name,
 string source = null,
 int numBins = Defaults.NumBins,
 int minBinSize = Defaults.MinBinSize)
 {
 var args = new SupervisedBinArguments()
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.FastTree/FastTreeClassification.cs

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Expand Up@@ -338,10 +338,10 @@ public void AdjustTreeOutputs(IChannel ch, RegressionTree tree,

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeBinaryClassifier",
 Desc = FastTreeBinaryClassificationTrainer.Summary,
 Remarks = FastTreeBinaryClassificationTrainer.Remarks,
 UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeBinaryClassifier",
 Desc = FastTreeBinaryClassificationTrainer.Summary,
 Remarks = FastTreeBinaryClassificationTrainer.Remarks,
 UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
 ShortName = FastTreeBinaryClassificationTrainer.ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastTreeBinaryClassificationTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeRanking.cs

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Expand Up@@ -1096,10 +1096,10 @@ public static FastTreeRankingPredictor Create(IHostEnvironment env, ModelLoadCon

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRanker",
 Desc = FastTreeRankingTrainer.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRanker",
 Desc = FastTreeRankingTrainer.Summary,
 Remarks = FastTreeRankingTrainer.Remarks,
 UserName = FastTreeRankingTrainer.UserNameValue,
 UserName = FastTreeRankingTrainer.UserNameValue,
 ShortName = FastTreeRankingTrainer.ShortName)]
 public static CommonOutputs.RankingOutput TrainRanking(IHostEnvironment env, FastTreeRankingTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeRegression.cs

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Expand Up@@ -449,9 +449,9 @@ public static FastTreeRegressionPredictor Create(IHostEnvironment env, ModelLoad
 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRegressor",
 Desc = FastTreeRegressionTrainer.Summary,
 Remarks = FastTreeRegressionTrainer.Remarks,
 UserName = FastTreeRegressionTrainer.UserNameValue,
 Desc = FastTreeRegressionTrainer.Summary,
 Remarks = FastTreeRegressionTrainer.Remarks,
 UserName = FastTreeRegressionTrainer.UserNameValue,
 ShortName = FastTreeRegressionTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastTreeRegressionTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeTweedie.cs

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Expand Up@@ -463,9 +463,9 @@ protected override void Map(ref VBuffer<float> src, ref float dst)

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeTweedieRegressor",
 Desc = FastTreeTweedieTrainer.Summary,
 UserName = FastTreeTweedieTrainer.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeTweedieRegressor",
 Desc = FastTreeTweedieTrainer.Summary,
 UserName = FastTreeTweedieTrainer.UserNameValue,
 ShortName = FastTreeTweedieTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainTweedieRegression(IHostEnvironment env, FastTreeTweedieTrainer.Arguments input)
 {
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.FastTree/RandomForestClassification.cs

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Expand Up@@ -208,10 +208,10 @@ protected override void GetGradientInOneQuery(int query, int threadIndex)

 public static partial class FastForest
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastForestBinaryClassifier",
 Desc = FastForestClassification.Summary,
 Remarks = FastForestClassification.Remarks,
 UserName = FastForestClassification.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastForestBinaryClassifier",
 Desc = FastForestClassification.Summary,
 Remarks = FastForestClassification.Remarks,
 UserName = FastForestClassification.UserNameValue,
 ShortName = FastForestClassification.ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastForestClassification.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/RandomForestRegression.cs

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Expand Up@@ -280,10 +280,10 @@ public BasicImpl(Dataset trainData, Arguments args)

 public static partial class FastForest
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastForestRegressor",
 Desc = FastForestRegression.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FastForestRegressor",
 Desc = FastForestRegression.Summary,
 Remarks = FastForestRegression.Remarks,
 UserName = FastForestRegression.LoadNameValue,
 UserName = FastForestRegression.LoadNameValue,
 ShortName = FastForestRegression.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastForestRegression.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.KMeansClustering/KMeansPlusPlusTrainer.cs

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Expand Up@@ -233,10 +233,10 @@ private static int ComputeNumThreads(IHost host, int? argNumThreads)
 return Math.Max(1, maxThreads);
 }

 [TlcModule.EntryPoint(Name = "Trainers.KMeansPlusPlusClusterer",
 [TlcModule.EntryPoint(Name = "Trainers.KMeansPlusPlusClusterer",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.ClusteringOutput TrainKMeans(IHostEnvironment env, Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.PCA/PcaTrainer.cs

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Expand Up@@ -284,10 +284,10 @@ private static void PostProcess(VBuffer<Float>[] y, Float[] sigma, Float[] z, in
 }
 }

 [TlcModule.EntryPoint(Name = "Trainers.PcaAnomalyDetector",
 [TlcModule.EntryPoint(Name = "Trainers.PcaAnomalyDetector",
 Desc = "Train an PCA Anomaly model.",
 Remarks = PcaPredictor.Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.AnomalyDetectionOutput TrainPcaAnomaly(IHostEnvironment env, Arguments input)
 {
Expand Down

8 changes: 3 additions & 5 deletions
src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineTrainer.cs

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Expand Up@@ -11,9 +11,7 @@
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FactorizationMachine;
using Microsoft.ML.Runtime.Internal.CpuMath;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Model;
using Microsoft.ML.Runtime.Training;

[assembly: LoadableClass(FieldAwareFactorizationMachineTrainer.Summary, typeof(FieldAwareFactorizationMachineTrainer), typeof(FieldAwareFactorizationMachineTrainer.Arguments),
Expand DownExpand Up@@ -413,10 +411,10 @@ public override FieldAwareFactorizationMachinePredictor CreatePredictor()
 return _pred;
 }

 [TlcModule.EntryPoint(Name = "Trainers.FieldAwareFactorizationMachineBinaryClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FieldAwareFactorizationMachineBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserName,
 UserName = UserName,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.StandardLearners/Standard/LinearClassificationTrainer.cs

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Expand Up@@ -189,7 +189,7 @@ public abstract class ArgumentsBase : LearnerInputBaseWithLabel
 public int? MaxIterations;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 public bool Shuffle = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Convergence check frequency (in terms of number of iterations). Set as negative or zero for not checking at all. If left blank, it defaults to check after every 'numThreads' iterations.", NullName = "<Auto>", ShortName = "checkFreq")]
Expand DownExpand Up@@ -1507,7 +1507,7 @@ public sealed class Arguments : LearnerInputBaseWithWeight
 public Double InitLearningRate = 0.01;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 public bool Shuffle = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Apply weight to the positive class, for imbalanced data", ShortName = "piw")]
Expand DownExpand Up@@ -1795,10 +1795,10 @@ public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironm
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentBinaryClassifier",
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentBinaryClassifier",
 Desc = "Train an SDCA binary model.",
 Remarks = LinearClassificationTrainer.Remarks,
 UserName = LinearClassificationTrainer.UserNameValue,
 UserName = LinearClassificationTrainer.UserNameValue,
 ShortName = LinearClassificationTrainer.LoadNameValue)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, LinearClassificationTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LogisticRegression.cs

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Expand Up@@ -386,10 +386,10 @@ public override ParameterMixingCalibratedPredictor CreatePredictor()
 new PlattCalibrator(Host, -1, 0));
 }

 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionBinaryClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
...Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs

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Expand Up@@ -961,10 +961,10 @@ public IRow GetStatsIRowOrNull(RoleMappedSchema schema)
 /// </summary>
 public partial class LogisticRegression
 {
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionClassifier",
 Desc = Summary,
 Remarks = MulticlassLogisticRegression.Remarks,
 UserName = MulticlassLogisticRegression.UserNameValue,
 UserName = MulticlassLogisticRegression.UserNameValue,
 ShortName = MulticlassLogisticRegression.ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClass(IHostEnvironment env, MulticlassLogisticRegression.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/MultiClass/MultiClassNaiveBayesTrainer.cs

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Expand Up@@ -130,8 +130,8 @@ public override MultiClassNaiveBayesPredictor CreatePredictor()
 return _predictor;
 }

 [TlcModule.EntryPoint(Name = "Trainers.NaiveBayesClassifier",
 Desc = "Train a MultiClassNaiveBayesTrainer.",
 [TlcModule.EntryPoint(Name = "Trainers.NaiveBayesClassifier",
 Desc = "Train a MultiClassNaiveBayesTrainer.",
 UserName = UserName, ShortName = ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClassNaiveBayesTrainer(IHostEnvironment env, Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/Online/AveragedPerceptron.cs

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Expand Up@@ -110,10 +110,10 @@ public override LinearBinaryPredictor CreatePredictor()
 return new LinearBinaryPredictor(Host, ref weights, bias);
 }

 [TlcModule.EntryPoint(Name = "Trainers.AveragedPerceptronBinaryClassifier",
 [TlcModule.EntryPoint(Name = "Trainers.AveragedPerceptronBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.StandardLearners/Standard/Online/OnlineGradientDescent.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -94,7 +94,7 @@ public override TPredictor CreatePredictor()
 return new LinearRegressionPredictor(Host, ref weights, bias);
 }

 [TlcModule.EntryPoint(Name = "Trainers.OnlineGradientDescentRegressor",
 [TlcModule.EntryPoint(Name = "Trainers.OnlineGradientDescentRegressor",
 Desc = "Train a Online gradient descent perceptron.",
 Remarks = Remarks,
 UserName = UserNameValue,
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.StandardLearners/Standard/PoissonRegression/PoissonRegression.cs

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Expand Up@@ -32,7 +32,7 @@ public sealed class PoissonRegression : LbfgsTrainerBase<Float, PoissonRegressio
 internal const string UserNameValue = "Poisson Regression";
 internal const string ShortName = "PR";
 internal const string Summary = "Poisson Regression assumes the unknown function, denoted Y has a Poisson distribution.";
new internal const string Remarks = @"<remarks>
 internal new const string Remarks = @"<remarks>
@zeahmedzeahmedJul 3, 2018

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@Ivanidzo4ka, It has be reverted here as well...:)

I have opened PR (486) to fix it.
<a href='https://en.wikipedia.org/wiki/Poisson_regression'>Poisson regression</a> is a parameterized regression method. 
It assumes that the log of the conditional mean of the dependent variable follows a linear function of the dependent variables. 
Assuming that the dependent variable follows a Poisson distribution, the parameters of the regressor can be estimated by maximizing the likelihood of the obtained observations.
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.StandardLearners/Standard/SdcaMultiClass.cs

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Expand Up@@ -386,10 +386,10 @@ protected override Float GetInstanceWeight(FloatLabelCursor cursor)
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentClassifier",
 Desc = SdcaMultiClassTrainer.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentClassifier",
 Desc = SdcaMultiClassTrainer.Summary,
 Remarks = SdcaMultiClassTrainer.Remarks,
 UserName = SdcaMultiClassTrainer.UserNameValue,
 UserName = SdcaMultiClassTrainer.UserNameValue,
 ShortName = SdcaMultiClassTrainer.ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClass(IHostEnvironment env, SdcaMultiClassTrainer.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/SdcaRegression.cs

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Expand Up@@ -131,10 +131,10 @@ protected override Float TuneDefaultL2(IChannel ch, int maxIterations, long rowC
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentRegressor",
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentRegressor",
 Desc = SdcaRegressionTrainer.Summary,
 Remarks = SdcaRegressionTrainer.Remarks,
 UserName = SdcaRegressionTrainer.UserNameValue,
 UserName = SdcaRegressionTrainer.UserNameValue,
 ShortName = SdcaRegressionTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, SdcaRegressionTrainer.Arguments input)
 {
Expand Down

10 changes: 5 additions & 5 deletions
src/Microsoft.ML.Transforms/BootstrapSampleTransform.cs

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Expand Up@@ -92,11 +92,11 @@ public BootstrapSampleTransform(IHostEnvironment env, Arguments args, IDataView
 /// <param name="seed">The random seed. If unspecified random state will be instead derived from the environment.</param>
 /// <param name="shuffleInput">Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.</param>
 /// <param name="poolSize">When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.</param>
 public BootstrapSampleTransform(IHostEnvironment env,
 IDataView input,
 bool complement = Defaults.Complement,
 uint? seed = null,
 bool shuffleInput = Defaults.ShuffleInput,
 public BootstrapSampleTransform(IHostEnvironment env,
 IDataView input,
 bool complement = Defaults.Complement,
 uint? seed = null,
 bool shuffleInput = Defaults.ShuffleInput,
 int poolSize = Defaults.PoolSize)
 : this(env, new Arguments() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
 {
Expand Down
Loading

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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 Merged

TomFinley
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Jul 3, 2018
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Remove all spaces in the end of lines
#478
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be612a5

remove all spaces in the end of lines

Jul 2, 2018
fff1041

revert new word placement

Jul 3, 2018
8d72c37

Merge branch 'master' into ivanidze/robotom_pacification

Jul 3, 2018

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36 changes: 18 additions & 18 deletions
src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -271,10 +271,10 @@ public static NormalizeTransform Create(IHostEnvironment env, MinMaxArguments ar
 /// <param name="name">Name of the output column.</param>
 /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
 /// /// <param name="useCdf">Whether to use CDF as the output.</param>
 public static NormalizeTransform CreateMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 bool useCdf = Defaults.MeanVarCdf)
 {
 var args = new MeanVarArguments()
Expand DownExpand Up@@ -313,10 +313,10 @@ public static NormalizeTransform Create(IHostEnvironment env, MeanVarArguments a
 /// <param name="name">Name of the output column.</param>
 /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
 /// /// <param name="useCdf">Whether to use CDF as the output.</param>
 public static NormalizeTransform CreateLogMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateLogMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 bool useCdf = Defaults.LogMeanVarCdf)
 {
 var args = new LogMeanVarArguments()
Expand DownExpand Up@@ -347,10 +347,10 @@ public static NormalizeTransform Create(IHostEnvironment env, LogMeanVarArgument
 return func;
 }

 public static NormalizeTransform CreateBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 int numBins = Defaults.NumBins)
 {
 var args = new BinArguments()
Expand DownExpand Up@@ -381,12 +381,12 @@ public static NormalizeTransform Create(IHostEnvironment env, BinArguments args,
 return func;
 }

 public static NormalizeTransform CreateSupervisedBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string labelColumn,
 string name,
 string source = null,
 int numBins = Defaults.NumBins,
 public static NormalizeTransform CreateSupervisedBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string labelColumn,
 string name,
 string source = null,
 int numBins = Defaults.NumBins,
 int minBinSize = Defaults.MinBinSize)
 {
 var args = new SupervisedBinArguments()
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.FastTree/FastTreeClassification.cs

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Expand Up@@ -338,10 +338,10 @@ public void AdjustTreeOutputs(IChannel ch, RegressionTree tree,

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeBinaryClassifier",
 Desc = FastTreeBinaryClassificationTrainer.Summary,
 Remarks = FastTreeBinaryClassificationTrainer.Remarks,
 UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeBinaryClassifier",
 Desc = FastTreeBinaryClassificationTrainer.Summary,
 Remarks = FastTreeBinaryClassificationTrainer.Remarks,
 UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
 ShortName = FastTreeBinaryClassificationTrainer.ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastTreeBinaryClassificationTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeRanking.cs

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Expand Up@@ -1096,10 +1096,10 @@ public static FastTreeRankingPredictor Create(IHostEnvironment env, ModelLoadCon

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRanker",
 Desc = FastTreeRankingTrainer.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRanker",
 Desc = FastTreeRankingTrainer.Summary,
 Remarks = FastTreeRankingTrainer.Remarks,
 UserName = FastTreeRankingTrainer.UserNameValue,
 UserName = FastTreeRankingTrainer.UserNameValue,
 ShortName = FastTreeRankingTrainer.ShortName)]
 public static CommonOutputs.RankingOutput TrainRanking(IHostEnvironment env, FastTreeRankingTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeRegression.cs

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Expand Up@@ -449,9 +449,9 @@ public static FastTreeRegressionPredictor Create(IHostEnvironment env, ModelLoad
 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRegressor",
 Desc = FastTreeRegressionTrainer.Summary,
 Remarks = FastTreeRegressionTrainer.Remarks,
 UserName = FastTreeRegressionTrainer.UserNameValue,
 Desc = FastTreeRegressionTrainer.Summary,
 Remarks = FastTreeRegressionTrainer.Remarks,
 UserName = FastTreeRegressionTrainer.UserNameValue,
 ShortName = FastTreeRegressionTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastTreeRegressionTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeTweedie.cs

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Expand Up@@ -463,9 +463,9 @@ protected override void Map(ref VBuffer<float> src, ref float dst)

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeTweedieRegressor",
 Desc = FastTreeTweedieTrainer.Summary,
 UserName = FastTreeTweedieTrainer.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeTweedieRegressor",
 Desc = FastTreeTweedieTrainer.Summary,
 UserName = FastTreeTweedieTrainer.UserNameValue,
 ShortName = FastTreeTweedieTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainTweedieRegression(IHostEnvironment env, FastTreeTweedieTrainer.Arguments input)
 {
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.FastTree/RandomForestClassification.cs

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Expand Up@@ -208,10 +208,10 @@ protected override void GetGradientInOneQuery(int query, int threadIndex)

 public static partial class FastForest
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastForestBinaryClassifier",
 Desc = FastForestClassification.Summary,
 Remarks = FastForestClassification.Remarks,
 UserName = FastForestClassification.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastForestBinaryClassifier",
 Desc = FastForestClassification.Summary,
 Remarks = FastForestClassification.Remarks,
 UserName = FastForestClassification.UserNameValue,
 ShortName = FastForestClassification.ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastForestClassification.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/RandomForestRegression.cs

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Expand Up@@ -280,10 +280,10 @@ public BasicImpl(Dataset trainData, Arguments args)

 public static partial class FastForest
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastForestRegressor",
 Desc = FastForestRegression.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FastForestRegressor",
 Desc = FastForestRegression.Summary,
 Remarks = FastForestRegression.Remarks,
 UserName = FastForestRegression.LoadNameValue,
 UserName = FastForestRegression.LoadNameValue,
 ShortName = FastForestRegression.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastForestRegression.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.KMeansClustering/KMeansPlusPlusTrainer.cs

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Expand Up@@ -233,10 +233,10 @@ private static int ComputeNumThreads(IHost host, int? argNumThreads)
 return Math.Max(1, maxThreads);
 }

 [TlcModule.EntryPoint(Name = "Trainers.KMeansPlusPlusClusterer",
 [TlcModule.EntryPoint(Name = "Trainers.KMeansPlusPlusClusterer",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.ClusteringOutput TrainKMeans(IHostEnvironment env, Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.PCA/PcaTrainer.cs

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Expand Up@@ -284,10 +284,10 @@ private static void PostProcess(VBuffer<Float>[] y, Float[] sigma, Float[] z, in
 }
 }

 [TlcModule.EntryPoint(Name = "Trainers.PcaAnomalyDetector",
 [TlcModule.EntryPoint(Name = "Trainers.PcaAnomalyDetector",
 Desc = "Train an PCA Anomaly model.",
 Remarks = PcaPredictor.Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.AnomalyDetectionOutput TrainPcaAnomaly(IHostEnvironment env, Arguments input)
 {
Expand Down

8 changes: 3 additions & 5 deletions
src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineTrainer.cs

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Expand Up@@ -11,9 +11,7 @@
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FactorizationMachine;
using Microsoft.ML.Runtime.Internal.CpuMath;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Model;
using Microsoft.ML.Runtime.Training;

[assembly: LoadableClass(FieldAwareFactorizationMachineTrainer.Summary, typeof(FieldAwareFactorizationMachineTrainer), typeof(FieldAwareFactorizationMachineTrainer.Arguments),
Expand DownExpand Up@@ -413,10 +411,10 @@ public override FieldAwareFactorizationMachinePredictor CreatePredictor()
 return _pred;
 }

 [TlcModule.EntryPoint(Name = "Trainers.FieldAwareFactorizationMachineBinaryClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FieldAwareFactorizationMachineBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserName,
 UserName = UserName,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.StandardLearners/Standard/LinearClassificationTrainer.cs

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Expand Up@@ -189,7 +189,7 @@ public abstract class ArgumentsBase : LearnerInputBaseWithLabel
 public int? MaxIterations;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 public bool Shuffle = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Convergence check frequency (in terms of number of iterations). Set as negative or zero for not checking at all. If left blank, it defaults to check after every 'numThreads' iterations.", NullName = "<Auto>", ShortName = "checkFreq")]
Expand DownExpand Up@@ -1507,7 +1507,7 @@ public sealed class Arguments : LearnerInputBaseWithWeight
 public Double InitLearningRate = 0.01;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 public bool Shuffle = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Apply weight to the positive class, for imbalanced data", ShortName = "piw")]
Expand DownExpand Up@@ -1795,10 +1795,10 @@ public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironm
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentBinaryClassifier",
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentBinaryClassifier",
 Desc = "Train an SDCA binary model.",
 Remarks = LinearClassificationTrainer.Remarks,
 UserName = LinearClassificationTrainer.UserNameValue,
 UserName = LinearClassificationTrainer.UserNameValue,
 ShortName = LinearClassificationTrainer.LoadNameValue)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, LinearClassificationTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LogisticRegression.cs

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Expand Up@@ -386,10 +386,10 @@ public override ParameterMixingCalibratedPredictor CreatePredictor()
 new PlattCalibrator(Host, -1, 0));
 }

 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionBinaryClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
...Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs

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Expand Up@@ -961,10 +961,10 @@ public IRow GetStatsIRowOrNull(RoleMappedSchema schema)
 /// </summary>
 public partial class LogisticRegression
 {
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionClassifier",
 Desc = Summary,
 Remarks = MulticlassLogisticRegression.Remarks,
 UserName = MulticlassLogisticRegression.UserNameValue,
 UserName = MulticlassLogisticRegression.UserNameValue,
 ShortName = MulticlassLogisticRegression.ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClass(IHostEnvironment env, MulticlassLogisticRegression.Arguments input)
 {
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4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/MultiClass/MultiClassNaiveBayesTrainer.cs

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Expand Up@@ -130,8 +130,8 @@ public override MultiClassNaiveBayesPredictor CreatePredictor()
 return _predictor;
 }

 [TlcModule.EntryPoint(Name = "Trainers.NaiveBayesClassifier",
 Desc = "Train a MultiClassNaiveBayesTrainer.",
 [TlcModule.EntryPoint(Name = "Trainers.NaiveBayesClassifier",
 Desc = "Train a MultiClassNaiveBayesTrainer.",
 UserName = UserName, ShortName = ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClassNaiveBayesTrainer(IHostEnvironment env, Arguments input)
 {
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4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/Online/AveragedPerceptron.cs

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Expand Up@@ -110,10 +110,10 @@ public override LinearBinaryPredictor CreatePredictor()
 return new LinearBinaryPredictor(Host, ref weights, bias);
 }

 [TlcModule.EntryPoint(Name = "Trainers.AveragedPerceptronBinaryClassifier",
 [TlcModule.EntryPoint(Name = "Trainers.AveragedPerceptronBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
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2 changes: 1 addition & 1 deletion
src/Microsoft.ML.StandardLearners/Standard/Online/OnlineGradientDescent.cs

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Expand Up@@ -94,7 +94,7 @@ public override TPredictor CreatePredictor()
 return new LinearRegressionPredictor(Host, ref weights, bias);
 }

 [TlcModule.EntryPoint(Name = "Trainers.OnlineGradientDescentRegressor",
 [TlcModule.EntryPoint(Name = "Trainers.OnlineGradientDescentRegressor",
 Desc = "Train a Online gradient descent perceptron.",
 Remarks = Remarks,
 UserName = UserNameValue,
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2 changes: 1 addition & 1 deletion
src/Microsoft.ML.StandardLearners/Standard/PoissonRegression/PoissonRegression.cs

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Expand Up@@ -32,7 +32,7 @@ public sealed class PoissonRegression : LbfgsTrainerBase<Float, PoissonRegressio
 internal const string UserNameValue = "Poisson Regression";
 internal const string ShortName = "PR";
 internal const string Summary = "Poisson Regression assumes the unknown function, denoted Y has a Poisson distribution.";
new internal const string Remarks = @"<remarks>
 internal new const string Remarks = @"<remarks>
@zeahmedzeahmedJul 3, 2018

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@Ivanidzo4ka, It has be reverted here as well...:)

I have opened PR (486) to fix it.
<a href='https://en.wikipedia.org/wiki/Poisson_regression'>Poisson regression</a> is a parameterized regression method. 
It assumes that the log of the conditional mean of the dependent variable follows a linear function of the dependent variables. 
Assuming that the dependent variable follows a Poisson distribution, the parameters of the regressor can be estimated by maximizing the likelihood of the obtained observations.
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6 changes: 3 additions & 3 deletions
src/Microsoft.ML.StandardLearners/Standard/SdcaMultiClass.cs

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Expand Up@@ -386,10 +386,10 @@ protected override Float GetInstanceWeight(FloatLabelCursor cursor)
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentClassifier",
 Desc = SdcaMultiClassTrainer.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentClassifier",
 Desc = SdcaMultiClassTrainer.Summary,
 Remarks = SdcaMultiClassTrainer.Remarks,
 UserName = SdcaMultiClassTrainer.UserNameValue,
 UserName = SdcaMultiClassTrainer.UserNameValue,
 ShortName = SdcaMultiClassTrainer.ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClass(IHostEnvironment env, SdcaMultiClassTrainer.Arguments input)
 {
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4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/SdcaRegression.cs

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Expand Up@@ -131,10 +131,10 @@ protected override Float TuneDefaultL2(IChannel ch, int maxIterations, long rowC
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentRegressor",
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentRegressor",
 Desc = SdcaRegressionTrainer.Summary,
 Remarks = SdcaRegressionTrainer.Remarks,
 UserName = SdcaRegressionTrainer.UserNameValue,
 UserName = SdcaRegressionTrainer.UserNameValue,
 ShortName = SdcaRegressionTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, SdcaRegressionTrainer.Arguments input)
 {
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10 changes: 5 additions & 5 deletions
src/Microsoft.ML.Transforms/BootstrapSampleTransform.cs

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Expand Up@@ -92,11 +92,11 @@ public BootstrapSampleTransform(IHostEnvironment env, Arguments args, IDataView
 /// <param name="seed">The random seed. If unspecified random state will be instead derived from the environment.</param>
 /// <param name="shuffleInput">Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.</param>
 /// <param name="poolSize">When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.</param>
 public BootstrapSampleTransform(IHostEnvironment env,
 IDataView input,
 bool complement = Defaults.Complement,
 uint? seed = null,
 bool shuffleInput = Defaults.ShuffleInput,
 public BootstrapSampleTransform(IHostEnvironment env,
 IDataView input,
 bool complement = Defaults.Complement,
 uint? seed = null,
 bool shuffleInput = Defaults.ShuffleInput,
 int poolSize = Defaults.PoolSize)
 : this(env, new Arguments() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
 {
Expand Down
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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TomFinley
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Jul 3, 2018
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Remove all spaces in the end of lines
#478
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be612a5

remove all spaces in the end of lines

Jul 2, 2018
fff1041

revert new word placement

Jul 3, 2018
8d72c37

Merge branch 'master' into ivanidze/robotom_pacification

Jul 3, 2018

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36 changes: 18 additions & 18 deletions
src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -271,10 +271,10 @@ public static NormalizeTransform Create(IHostEnvironment env, MinMaxArguments ar
 /// <param name="name">Name of the output column.</param>
 /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
 /// /// <param name="useCdf">Whether to use CDF as the output.</param>
 public static NormalizeTransform CreateMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 bool useCdf = Defaults.MeanVarCdf)
 {
 var args = new MeanVarArguments()
Expand DownExpand Up@@ -313,10 +313,10 @@ public static NormalizeTransform Create(IHostEnvironment env, MeanVarArguments a
 /// <param name="name">Name of the output column.</param>
 /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
 /// /// <param name="useCdf">Whether to use CDF as the output.</param>
 public static NormalizeTransform CreateLogMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateLogMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 bool useCdf = Defaults.LogMeanVarCdf)
 {
 var args = new LogMeanVarArguments()
Expand DownExpand Up@@ -347,10 +347,10 @@ public static NormalizeTransform Create(IHostEnvironment env, LogMeanVarArgument
 return func;
 }

 public static NormalizeTransform CreateBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 int numBins = Defaults.NumBins)
 {
 var args = new BinArguments()
Expand DownExpand Up@@ -381,12 +381,12 @@ public static NormalizeTransform Create(IHostEnvironment env, BinArguments args,
 return func;
 }

 public static NormalizeTransform CreateSupervisedBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string labelColumn,
 string name,
 string source = null,
 int numBins = Defaults.NumBins,
 public static NormalizeTransform CreateSupervisedBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string labelColumn,
 string name,
 string source = null,
 int numBins = Defaults.NumBins,
 int minBinSize = Defaults.MinBinSize)
 {
 var args = new SupervisedBinArguments()
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.FastTree/FastTreeClassification.cs

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Expand Up@@ -338,10 +338,10 @@ public void AdjustTreeOutputs(IChannel ch, RegressionTree tree,

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeBinaryClassifier",
 Desc = FastTreeBinaryClassificationTrainer.Summary,
 Remarks = FastTreeBinaryClassificationTrainer.Remarks,
 UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeBinaryClassifier",
 Desc = FastTreeBinaryClassificationTrainer.Summary,
 Remarks = FastTreeBinaryClassificationTrainer.Remarks,
 UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
 ShortName = FastTreeBinaryClassificationTrainer.ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastTreeBinaryClassificationTrainer.Arguments input)
 {
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6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeRanking.cs

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Expand Up@@ -1096,10 +1096,10 @@ public static FastTreeRankingPredictor Create(IHostEnvironment env, ModelLoadCon

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRanker",
 Desc = FastTreeRankingTrainer.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRanker",
 Desc = FastTreeRankingTrainer.Summary,
 Remarks = FastTreeRankingTrainer.Remarks,
 UserName = FastTreeRankingTrainer.UserNameValue,
 UserName = FastTreeRankingTrainer.UserNameValue,
 ShortName = FastTreeRankingTrainer.ShortName)]
 public static CommonOutputs.RankingOutput TrainRanking(IHostEnvironment env, FastTreeRankingTrainer.Arguments input)
 {
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6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeRegression.cs

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Expand Up@@ -449,9 +449,9 @@ public static FastTreeRegressionPredictor Create(IHostEnvironment env, ModelLoad
 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRegressor",
 Desc = FastTreeRegressionTrainer.Summary,
 Remarks = FastTreeRegressionTrainer.Remarks,
 UserName = FastTreeRegressionTrainer.UserNameValue,
 Desc = FastTreeRegressionTrainer.Summary,
 Remarks = FastTreeRegressionTrainer.Remarks,
 UserName = FastTreeRegressionTrainer.UserNameValue,
 ShortName = FastTreeRegressionTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastTreeRegressionTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeTweedie.cs

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Expand Up@@ -463,9 +463,9 @@ protected override void Map(ref VBuffer<float> src, ref float dst)

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeTweedieRegressor",
 Desc = FastTreeTweedieTrainer.Summary,
 UserName = FastTreeTweedieTrainer.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeTweedieRegressor",
 Desc = FastTreeTweedieTrainer.Summary,
 UserName = FastTreeTweedieTrainer.UserNameValue,
 ShortName = FastTreeTweedieTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainTweedieRegression(IHostEnvironment env, FastTreeTweedieTrainer.Arguments input)
 {
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.FastTree/RandomForestClassification.cs

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Expand Up@@ -208,10 +208,10 @@ protected override void GetGradientInOneQuery(int query, int threadIndex)

 public static partial class FastForest
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastForestBinaryClassifier",
 Desc = FastForestClassification.Summary,
 Remarks = FastForestClassification.Remarks,
 UserName = FastForestClassification.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastForestBinaryClassifier",
 Desc = FastForestClassification.Summary,
 Remarks = FastForestClassification.Remarks,
 UserName = FastForestClassification.UserNameValue,
 ShortName = FastForestClassification.ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastForestClassification.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/RandomForestRegression.cs

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Expand Up@@ -280,10 +280,10 @@ public BasicImpl(Dataset trainData, Arguments args)

 public static partial class FastForest
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastForestRegressor",
 Desc = FastForestRegression.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FastForestRegressor",
 Desc = FastForestRegression.Summary,
 Remarks = FastForestRegression.Remarks,
 UserName = FastForestRegression.LoadNameValue,
 UserName = FastForestRegression.LoadNameValue,
 ShortName = FastForestRegression.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastForestRegression.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.KMeansClustering/KMeansPlusPlusTrainer.cs

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Expand Up@@ -233,10 +233,10 @@ private static int ComputeNumThreads(IHost host, int? argNumThreads)
 return Math.Max(1, maxThreads);
 }

 [TlcModule.EntryPoint(Name = "Trainers.KMeansPlusPlusClusterer",
 [TlcModule.EntryPoint(Name = "Trainers.KMeansPlusPlusClusterer",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.ClusteringOutput TrainKMeans(IHostEnvironment env, Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.PCA/PcaTrainer.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -284,10 +284,10 @@ private static void PostProcess(VBuffer<Float>[] y, Float[] sigma, Float[] z, in
 }
 }

 [TlcModule.EntryPoint(Name = "Trainers.PcaAnomalyDetector",
 [TlcModule.EntryPoint(Name = "Trainers.PcaAnomalyDetector",
 Desc = "Train an PCA Anomaly model.",
 Remarks = PcaPredictor.Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.AnomalyDetectionOutput TrainPcaAnomaly(IHostEnvironment env, Arguments input)
 {
Expand Down

8 changes: 3 additions & 5 deletions
src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineTrainer.cs

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Expand Up@@ -11,9 +11,7 @@
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FactorizationMachine;
using Microsoft.ML.Runtime.Internal.CpuMath;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Model;
using Microsoft.ML.Runtime.Training;

[assembly: LoadableClass(FieldAwareFactorizationMachineTrainer.Summary, typeof(FieldAwareFactorizationMachineTrainer), typeof(FieldAwareFactorizationMachineTrainer.Arguments),
Expand DownExpand Up@@ -413,10 +411,10 @@ public override FieldAwareFactorizationMachinePredictor CreatePredictor()
 return _pred;
 }

 [TlcModule.EntryPoint(Name = "Trainers.FieldAwareFactorizationMachineBinaryClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FieldAwareFactorizationMachineBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserName,
 UserName = UserName,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.StandardLearners/Standard/LinearClassificationTrainer.cs

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Expand Up@@ -189,7 +189,7 @@ public abstract class ArgumentsBase : LearnerInputBaseWithLabel
 public int? MaxIterations;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 public bool Shuffle = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Convergence check frequency (in terms of number of iterations). Set as negative or zero for not checking at all. If left blank, it defaults to check after every 'numThreads' iterations.", NullName = "<Auto>", ShortName = "checkFreq")]
Expand DownExpand Up@@ -1507,7 +1507,7 @@ public sealed class Arguments : LearnerInputBaseWithWeight
 public Double InitLearningRate = 0.01;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 public bool Shuffle = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Apply weight to the positive class, for imbalanced data", ShortName = "piw")]
Expand DownExpand Up@@ -1795,10 +1795,10 @@ public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironm
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentBinaryClassifier",
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentBinaryClassifier",
 Desc = "Train an SDCA binary model.",
 Remarks = LinearClassificationTrainer.Remarks,
 UserName = LinearClassificationTrainer.UserNameValue,
 UserName = LinearClassificationTrainer.UserNameValue,
 ShortName = LinearClassificationTrainer.LoadNameValue)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, LinearClassificationTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LogisticRegression.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -386,10 +386,10 @@ public override ParameterMixingCalibratedPredictor CreatePredictor()
 new PlattCalibrator(Host, -1, 0));
 }

 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionBinaryClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
...Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -961,10 +961,10 @@ public IRow GetStatsIRowOrNull(RoleMappedSchema schema)
 /// </summary>
 public partial class LogisticRegression
 {
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionClassifier",
 Desc = Summary,
 Remarks = MulticlassLogisticRegression.Remarks,
 UserName = MulticlassLogisticRegression.UserNameValue,
 UserName = MulticlassLogisticRegression.UserNameValue,
 ShortName = MulticlassLogisticRegression.ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClass(IHostEnvironment env, MulticlassLogisticRegression.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/MultiClass/MultiClassNaiveBayesTrainer.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -130,8 +130,8 @@ public override MultiClassNaiveBayesPredictor CreatePredictor()
 return _predictor;
 }

 [TlcModule.EntryPoint(Name = "Trainers.NaiveBayesClassifier",
 Desc = "Train a MultiClassNaiveBayesTrainer.",
 [TlcModule.EntryPoint(Name = "Trainers.NaiveBayesClassifier",
 Desc = "Train a MultiClassNaiveBayesTrainer.",
 UserName = UserName, ShortName = ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClassNaiveBayesTrainer(IHostEnvironment env, Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/Online/AveragedPerceptron.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -110,10 +110,10 @@ public override LinearBinaryPredictor CreatePredictor()
 return new LinearBinaryPredictor(Host, ref weights, bias);
 }

 [TlcModule.EntryPoint(Name = "Trainers.AveragedPerceptronBinaryClassifier",
 [TlcModule.EntryPoint(Name = "Trainers.AveragedPerceptronBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.StandardLearners/Standard/Online/OnlineGradientDescent.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -94,7 +94,7 @@ public override TPredictor CreatePredictor()
 return new LinearRegressionPredictor(Host, ref weights, bias);
 }

 [TlcModule.EntryPoint(Name = "Trainers.OnlineGradientDescentRegressor",
 [TlcModule.EntryPoint(Name = "Trainers.OnlineGradientDescentRegressor",
 Desc = "Train a Online gradient descent perceptron.",
 Remarks = Remarks,
 UserName = UserNameValue,
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.StandardLearners/Standard/PoissonRegression/PoissonRegression.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -32,7 +32,7 @@ public sealed class PoissonRegression : LbfgsTrainerBase<Float, PoissonRegressio
 internal const string UserNameValue = "Poisson Regression";
 internal const string ShortName = "PR";
 internal const string Summary = "Poisson Regression assumes the unknown function, denoted Y has a Poisson distribution.";
new internal const string Remarks = @"<remarks>
 internal new const string Remarks = @"<remarks>
@zeahmedzeahmedJul 3, 2018

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Contributor
Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

@Ivanidzo4ka, It has be reverted here as well...:)

I have opened PR (486) to fix it.
<a href='https://en.wikipedia.org/wiki/Poisson_regression'>Poisson regression</a> is a parameterized regression method. 
It assumes that the log of the conditional mean of the dependent variable follows a linear function of the dependent variables. 
Assuming that the dependent variable follows a Poisson distribution, the parameters of the regressor can be estimated by maximizing the likelihood of the obtained observations.
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.StandardLearners/Standard/SdcaMultiClass.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -386,10 +386,10 @@ protected override Float GetInstanceWeight(FloatLabelCursor cursor)
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentClassifier",
 Desc = SdcaMultiClassTrainer.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentClassifier",
 Desc = SdcaMultiClassTrainer.Summary,
 Remarks = SdcaMultiClassTrainer.Remarks,
 UserName = SdcaMultiClassTrainer.UserNameValue,
 UserName = SdcaMultiClassTrainer.UserNameValue,
 ShortName = SdcaMultiClassTrainer.ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClass(IHostEnvironment env, SdcaMultiClassTrainer.Arguments input)
 {
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4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/SdcaRegression.cs

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Expand Up@@ -131,10 +131,10 @@ protected override Float TuneDefaultL2(IChannel ch, int maxIterations, long rowC
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentRegressor",
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentRegressor",
 Desc = SdcaRegressionTrainer.Summary,
 Remarks = SdcaRegressionTrainer.Remarks,
 UserName = SdcaRegressionTrainer.UserNameValue,
 UserName = SdcaRegressionTrainer.UserNameValue,
 ShortName = SdcaRegressionTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, SdcaRegressionTrainer.Arguments input)
 {
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10 changes: 5 additions & 5 deletions
src/Microsoft.ML.Transforms/BootstrapSampleTransform.cs

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Expand Up@@ -92,11 +92,11 @@ public BootstrapSampleTransform(IHostEnvironment env, Arguments args, IDataView
 /// <param name="seed">The random seed. If unspecified random state will be instead derived from the environment.</param>
 /// <param name="shuffleInput">Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.</param>
 /// <param name="poolSize">When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.</param>
 public BootstrapSampleTransform(IHostEnvironment env,
 IDataView input,
 bool complement = Defaults.Complement,
 uint? seed = null,
 bool shuffleInput = Defaults.ShuffleInput,
 public BootstrapSampleTransform(IHostEnvironment env,
 IDataView input,
 bool complement = Defaults.Complement,
 uint? seed = null,
 bool shuffleInput = Defaults.ShuffleInput,
 int poolSize = Defaults.PoolSize)
 : this(env, new Arguments() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
 {
Expand Down
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TomFinley
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Jul 3, 2018
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Remove all spaces in the end of lines
#478
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be612a5

remove all spaces in the end of lines

Jul 2, 2018
fff1041

revert new word placement

Jul 3, 2018
8d72c37

Merge branch 'master' into ivanidze/robotom_pacification

Jul 3, 2018

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36 changes: 18 additions & 18 deletions
src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs

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Expand Up@@ -271,10 +271,10 @@ public static NormalizeTransform Create(IHostEnvironment env, MinMaxArguments ar
 /// <param name="name">Name of the output column.</param>
 /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
 /// /// <param name="useCdf">Whether to use CDF as the output.</param>
 public static NormalizeTransform CreateMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 bool useCdf = Defaults.MeanVarCdf)
 {
 var args = new MeanVarArguments()
Expand DownExpand Up@@ -313,10 +313,10 @@ public static NormalizeTransform Create(IHostEnvironment env, MeanVarArguments a
 /// <param name="name">Name of the output column.</param>
 /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
 /// /// <param name="useCdf">Whether to use CDF as the output.</param>
 public static NormalizeTransform CreateLogMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateLogMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 bool useCdf = Defaults.LogMeanVarCdf)
 {
 var args = new LogMeanVarArguments()
Expand DownExpand Up@@ -347,10 +347,10 @@ public static NormalizeTransform Create(IHostEnvironment env, LogMeanVarArgument
 return func;
 }

 public static NormalizeTransform CreateBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 int numBins = Defaults.NumBins)
 {
 var args = new BinArguments()
Expand DownExpand Up@@ -381,12 +381,12 @@ public static NormalizeTransform Create(IHostEnvironment env, BinArguments args,
 return func;
 }

 public static NormalizeTransform CreateSupervisedBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string labelColumn,
 string name,
 string source = null,
 int numBins = Defaults.NumBins,
 public static NormalizeTransform CreateSupervisedBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string labelColumn,
 string name,
 string source = null,
 int numBins = Defaults.NumBins,
 int minBinSize = Defaults.MinBinSize)
 {
 var args = new SupervisedBinArguments()
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.FastTree/FastTreeClassification.cs

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Expand Up@@ -338,10 +338,10 @@ public void AdjustTreeOutputs(IChannel ch, RegressionTree tree,

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeBinaryClassifier",
 Desc = FastTreeBinaryClassificationTrainer.Summary,
 Remarks = FastTreeBinaryClassificationTrainer.Remarks,
 UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeBinaryClassifier",
 Desc = FastTreeBinaryClassificationTrainer.Summary,
 Remarks = FastTreeBinaryClassificationTrainer.Remarks,
 UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
 ShortName = FastTreeBinaryClassificationTrainer.ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastTreeBinaryClassificationTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeRanking.cs

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Expand Up@@ -1096,10 +1096,10 @@ public static FastTreeRankingPredictor Create(IHostEnvironment env, ModelLoadCon

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRanker",
 Desc = FastTreeRankingTrainer.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRanker",
 Desc = FastTreeRankingTrainer.Summary,
 Remarks = FastTreeRankingTrainer.Remarks,
 UserName = FastTreeRankingTrainer.UserNameValue,
 UserName = FastTreeRankingTrainer.UserNameValue,
 ShortName = FastTreeRankingTrainer.ShortName)]
 public static CommonOutputs.RankingOutput TrainRanking(IHostEnvironment env, FastTreeRankingTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeRegression.cs

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Expand Up@@ -449,9 +449,9 @@ public static FastTreeRegressionPredictor Create(IHostEnvironment env, ModelLoad
 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRegressor",
 Desc = FastTreeRegressionTrainer.Summary,
 Remarks = FastTreeRegressionTrainer.Remarks,
 UserName = FastTreeRegressionTrainer.UserNameValue,
 Desc = FastTreeRegressionTrainer.Summary,
 Remarks = FastTreeRegressionTrainer.Remarks,
 UserName = FastTreeRegressionTrainer.UserNameValue,
 ShortName = FastTreeRegressionTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastTreeRegressionTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeTweedie.cs

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Expand Up@@ -463,9 +463,9 @@ protected override void Map(ref VBuffer<float> src, ref float dst)

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeTweedieRegressor",
 Desc = FastTreeTweedieTrainer.Summary,
 UserName = FastTreeTweedieTrainer.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeTweedieRegressor",
 Desc = FastTreeTweedieTrainer.Summary,
 UserName = FastTreeTweedieTrainer.UserNameValue,
 ShortName = FastTreeTweedieTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainTweedieRegression(IHostEnvironment env, FastTreeTweedieTrainer.Arguments input)
 {
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.FastTree/RandomForestClassification.cs

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Expand Up@@ -208,10 +208,10 @@ protected override void GetGradientInOneQuery(int query, int threadIndex)

 public static partial class FastForest
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastForestBinaryClassifier",
 Desc = FastForestClassification.Summary,
 Remarks = FastForestClassification.Remarks,
 UserName = FastForestClassification.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastForestBinaryClassifier",
 Desc = FastForestClassification.Summary,
 Remarks = FastForestClassification.Remarks,
 UserName = FastForestClassification.UserNameValue,
 ShortName = FastForestClassification.ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastForestClassification.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/RandomForestRegression.cs

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Expand Up@@ -280,10 +280,10 @@ public BasicImpl(Dataset trainData, Arguments args)

 public static partial class FastForest
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastForestRegressor",
 Desc = FastForestRegression.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FastForestRegressor",
 Desc = FastForestRegression.Summary,
 Remarks = FastForestRegression.Remarks,
 UserName = FastForestRegression.LoadNameValue,
 UserName = FastForestRegression.LoadNameValue,
 ShortName = FastForestRegression.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastForestRegression.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.KMeansClustering/KMeansPlusPlusTrainer.cs

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Expand Up@@ -233,10 +233,10 @@ private static int ComputeNumThreads(IHost host, int? argNumThreads)
 return Math.Max(1, maxThreads);
 }

 [TlcModule.EntryPoint(Name = "Trainers.KMeansPlusPlusClusterer",
 [TlcModule.EntryPoint(Name = "Trainers.KMeansPlusPlusClusterer",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.ClusteringOutput TrainKMeans(IHostEnvironment env, Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.PCA/PcaTrainer.cs

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Expand Up@@ -284,10 +284,10 @@ private static void PostProcess(VBuffer<Float>[] y, Float[] sigma, Float[] z, in
 }
 }

 [TlcModule.EntryPoint(Name = "Trainers.PcaAnomalyDetector",
 [TlcModule.EntryPoint(Name = "Trainers.PcaAnomalyDetector",
 Desc = "Train an PCA Anomaly model.",
 Remarks = PcaPredictor.Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.AnomalyDetectionOutput TrainPcaAnomaly(IHostEnvironment env, Arguments input)
 {
Expand Down

8 changes: 3 additions & 5 deletions
src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineTrainer.cs

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Expand Up@@ -11,9 +11,7 @@
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FactorizationMachine;
using Microsoft.ML.Runtime.Internal.CpuMath;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Model;
using Microsoft.ML.Runtime.Training;

[assembly: LoadableClass(FieldAwareFactorizationMachineTrainer.Summary, typeof(FieldAwareFactorizationMachineTrainer), typeof(FieldAwareFactorizationMachineTrainer.Arguments),
Expand DownExpand Up@@ -413,10 +411,10 @@ public override FieldAwareFactorizationMachinePredictor CreatePredictor()
 return _pred;
 }

 [TlcModule.EntryPoint(Name = "Trainers.FieldAwareFactorizationMachineBinaryClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FieldAwareFactorizationMachineBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserName,
 UserName = UserName,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.StandardLearners/Standard/LinearClassificationTrainer.cs

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Expand Up@@ -189,7 +189,7 @@ public abstract class ArgumentsBase : LearnerInputBaseWithLabel
 public int? MaxIterations;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 public bool Shuffle = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Convergence check frequency (in terms of number of iterations). Set as negative or zero for not checking at all. If left blank, it defaults to check after every 'numThreads' iterations.", NullName = "<Auto>", ShortName = "checkFreq")]
Expand DownExpand Up@@ -1507,7 +1507,7 @@ public sealed class Arguments : LearnerInputBaseWithWeight
 public Double InitLearningRate = 0.01;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 public bool Shuffle = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Apply weight to the positive class, for imbalanced data", ShortName = "piw")]
Expand DownExpand Up@@ -1795,10 +1795,10 @@ public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironm
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentBinaryClassifier",
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentBinaryClassifier",
 Desc = "Train an SDCA binary model.",
 Remarks = LinearClassificationTrainer.Remarks,
 UserName = LinearClassificationTrainer.UserNameValue,
 UserName = LinearClassificationTrainer.UserNameValue,
 ShortName = LinearClassificationTrainer.LoadNameValue)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, LinearClassificationTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LogisticRegression.cs

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Expand Up@@ -386,10 +386,10 @@ public override ParameterMixingCalibratedPredictor CreatePredictor()
 new PlattCalibrator(Host, -1, 0));
 }

 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionBinaryClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
...Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs

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Expand Up@@ -961,10 +961,10 @@ public IRow GetStatsIRowOrNull(RoleMappedSchema schema)
 /// </summary>
 public partial class LogisticRegression
 {
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionClassifier",
 Desc = Summary,
 Remarks = MulticlassLogisticRegression.Remarks,
 UserName = MulticlassLogisticRegression.UserNameValue,
 UserName = MulticlassLogisticRegression.UserNameValue,
 ShortName = MulticlassLogisticRegression.ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClass(IHostEnvironment env, MulticlassLogisticRegression.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/MultiClass/MultiClassNaiveBayesTrainer.cs

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Expand Up@@ -130,8 +130,8 @@ public override MultiClassNaiveBayesPredictor CreatePredictor()
 return _predictor;
 }

 [TlcModule.EntryPoint(Name = "Trainers.NaiveBayesClassifier",
 Desc = "Train a MultiClassNaiveBayesTrainer.",
 [TlcModule.EntryPoint(Name = "Trainers.NaiveBayesClassifier",
 Desc = "Train a MultiClassNaiveBayesTrainer.",
 UserName = UserName, ShortName = ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClassNaiveBayesTrainer(IHostEnvironment env, Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/Online/AveragedPerceptron.cs

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Expand Up@@ -110,10 +110,10 @@ public override LinearBinaryPredictor CreatePredictor()
 return new LinearBinaryPredictor(Host, ref weights, bias);
 }

 [TlcModule.EntryPoint(Name = "Trainers.AveragedPerceptronBinaryClassifier",
 [TlcModule.EntryPoint(Name = "Trainers.AveragedPerceptronBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.StandardLearners/Standard/Online/OnlineGradientDescent.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -94,7 +94,7 @@ public override TPredictor CreatePredictor()
 return new LinearRegressionPredictor(Host, ref weights, bias);
 }

 [TlcModule.EntryPoint(Name = "Trainers.OnlineGradientDescentRegressor",
 [TlcModule.EntryPoint(Name = "Trainers.OnlineGradientDescentRegressor",
 Desc = "Train a Online gradient descent perceptron.",
 Remarks = Remarks,
 UserName = UserNameValue,
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.StandardLearners/Standard/PoissonRegression/PoissonRegression.cs

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Expand Up@@ -32,7 +32,7 @@ public sealed class PoissonRegression : LbfgsTrainerBase<Float, PoissonRegressio
 internal const string UserNameValue = "Poisson Regression";
 internal const string ShortName = "PR";
 internal const string Summary = "Poisson Regression assumes the unknown function, denoted Y has a Poisson distribution.";
new internal const string Remarks = @"<remarks>
 internal new const string Remarks = @"<remarks>
@zeahmedzeahmedJul 3, 2018

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@Ivanidzo4ka, It has be reverted here as well...:)

I have opened PR (486) to fix it.
<a href='https://en.wikipedia.org/wiki/Poisson_regression'>Poisson regression</a> is a parameterized regression method. 
It assumes that the log of the conditional mean of the dependent variable follows a linear function of the dependent variables. 
Assuming that the dependent variable follows a Poisson distribution, the parameters of the regressor can be estimated by maximizing the likelihood of the obtained observations.
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.StandardLearners/Standard/SdcaMultiClass.cs

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Expand Up@@ -386,10 +386,10 @@ protected override Float GetInstanceWeight(FloatLabelCursor cursor)
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentClassifier",
 Desc = SdcaMultiClassTrainer.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentClassifier",
 Desc = SdcaMultiClassTrainer.Summary,
 Remarks = SdcaMultiClassTrainer.Remarks,
 UserName = SdcaMultiClassTrainer.UserNameValue,
 UserName = SdcaMultiClassTrainer.UserNameValue,
 ShortName = SdcaMultiClassTrainer.ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClass(IHostEnvironment env, SdcaMultiClassTrainer.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/SdcaRegression.cs

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Expand Up@@ -131,10 +131,10 @@ protected override Float TuneDefaultL2(IChannel ch, int maxIterations, long rowC
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentRegressor",
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentRegressor",
 Desc = SdcaRegressionTrainer.Summary,
 Remarks = SdcaRegressionTrainer.Remarks,
 UserName = SdcaRegressionTrainer.UserNameValue,
 UserName = SdcaRegressionTrainer.UserNameValue,
 ShortName = SdcaRegressionTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, SdcaRegressionTrainer.Arguments input)
 {
Expand Down

10 changes: 5 additions & 5 deletions
src/Microsoft.ML.Transforms/BootstrapSampleTransform.cs

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Expand Up@@ -92,11 +92,11 @@ public BootstrapSampleTransform(IHostEnvironment env, Arguments args, IDataView
 /// <param name="seed">The random seed. If unspecified random state will be instead derived from the environment.</param>
 /// <param name="shuffleInput">Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.</param>
 /// <param name="poolSize">When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.</param>
 public BootstrapSampleTransform(IHostEnvironment env,
 IDataView input,
 bool complement = Defaults.Complement,
 uint? seed = null,
 bool shuffleInput = Defaults.ShuffleInput,
 public BootstrapSampleTransform(IHostEnvironment env,
 IDataView input,
 bool complement = Defaults.Complement,
 uint? seed = null,
 bool shuffleInput = Defaults.ShuffleInput,
 int poolSize = Defaults.PoolSize)
 : this(env, new Arguments() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
 {
Expand Down
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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TomFinley
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Jul 3, 2018
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Remove all spaces in the end of lines
#478
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be612a5

remove all spaces in the end of lines

Jul 2, 2018
fff1041

revert new word placement

Jul 3, 2018
8d72c37

Merge branch 'master' into ivanidze/robotom_pacification

Jul 3, 2018

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36 changes: 18 additions & 18 deletions
src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs

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Expand Up@@ -271,10 +271,10 @@ public static NormalizeTransform Create(IHostEnvironment env, MinMaxArguments ar
 /// <param name="name">Name of the output column.</param>
 /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
 /// /// <param name="useCdf">Whether to use CDF as the output.</param>
 public static NormalizeTransform CreateMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 bool useCdf = Defaults.MeanVarCdf)
 {
 var args = new MeanVarArguments()
Expand DownExpand Up@@ -313,10 +313,10 @@ public static NormalizeTransform Create(IHostEnvironment env, MeanVarArguments a
 /// <param name="name">Name of the output column.</param>
 /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
 /// /// <param name="useCdf">Whether to use CDF as the output.</param>
 public static NormalizeTransform CreateLogMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateLogMeanVarNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 bool useCdf = Defaults.LogMeanVarCdf)
 {
 var args = new LogMeanVarArguments()
Expand DownExpand Up@@ -347,10 +347,10 @@ public static NormalizeTransform Create(IHostEnvironment env, LogMeanVarArgument
 return func;
 }

 public static NormalizeTransform CreateBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source=null,
 public static NormalizeTransform CreateBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string name,
 string source = null,
 int numBins = Defaults.NumBins)
 {
 var args = new BinArguments()
Expand DownExpand Up@@ -381,12 +381,12 @@ public static NormalizeTransform Create(IHostEnvironment env, BinArguments args,
 return func;
 }

 public static NormalizeTransform CreateSupervisedBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string labelColumn,
 string name,
 string source = null,
 int numBins = Defaults.NumBins,
 public static NormalizeTransform CreateSupervisedBinningNormalizer(IHostEnvironment env,
 IDataView input,
 string labelColumn,
 string name,
 string source = null,
 int numBins = Defaults.NumBins,
 int minBinSize = Defaults.MinBinSize)
 {
 var args = new SupervisedBinArguments()
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.FastTree/FastTreeClassification.cs

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Expand Up@@ -338,10 +338,10 @@ public void AdjustTreeOutputs(IChannel ch, RegressionTree tree,

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeBinaryClassifier",
 Desc = FastTreeBinaryClassificationTrainer.Summary,
 Remarks = FastTreeBinaryClassificationTrainer.Remarks,
 UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeBinaryClassifier",
 Desc = FastTreeBinaryClassificationTrainer.Summary,
 Remarks = FastTreeBinaryClassificationTrainer.Remarks,
 UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
 ShortName = FastTreeBinaryClassificationTrainer.ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastTreeBinaryClassificationTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeRanking.cs

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Expand Up@@ -1096,10 +1096,10 @@ public static FastTreeRankingPredictor Create(IHostEnvironment env, ModelLoadCon

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRanker",
 Desc = FastTreeRankingTrainer.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRanker",
 Desc = FastTreeRankingTrainer.Summary,
 Remarks = FastTreeRankingTrainer.Remarks,
 UserName = FastTreeRankingTrainer.UserNameValue,
 UserName = FastTreeRankingTrainer.UserNameValue,
 ShortName = FastTreeRankingTrainer.ShortName)]
 public static CommonOutputs.RankingOutput TrainRanking(IHostEnvironment env, FastTreeRankingTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeRegression.cs

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Expand Up@@ -449,9 +449,9 @@ public static FastTreeRegressionPredictor Create(IHostEnvironment env, ModelLoad
 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeRegressor",
 Desc = FastTreeRegressionTrainer.Summary,
 Remarks = FastTreeRegressionTrainer.Remarks,
 UserName = FastTreeRegressionTrainer.UserNameValue,
 Desc = FastTreeRegressionTrainer.Summary,
 Remarks = FastTreeRegressionTrainer.Remarks,
 UserName = FastTreeRegressionTrainer.UserNameValue,
 ShortName = FastTreeRegressionTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastTreeRegressionTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/FastTreeTweedie.cs

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Expand Up@@ -463,9 +463,9 @@ protected override void Map(ref VBuffer<float> src, ref float dst)

 public static partial class FastTree
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeTweedieRegressor",
 Desc = FastTreeTweedieTrainer.Summary,
 UserName = FastTreeTweedieTrainer.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastTreeTweedieRegressor",
 Desc = FastTreeTweedieTrainer.Summary,
 UserName = FastTreeTweedieTrainer.UserNameValue,
 ShortName = FastTreeTweedieTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainTweedieRegression(IHostEnvironment env, FastTreeTweedieTrainer.Arguments input)
 {
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.FastTree/RandomForestClassification.cs

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Expand Up@@ -208,10 +208,10 @@ protected override void GetGradientInOneQuery(int query, int threadIndex)

 public static partial class FastForest
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastForestBinaryClassifier",
 Desc = FastForestClassification.Summary,
 Remarks = FastForestClassification.Remarks,
 UserName = FastForestClassification.UserNameValue,
 [TlcModule.EntryPoint(Name = "Trainers.FastForestBinaryClassifier",
 Desc = FastForestClassification.Summary,
 Remarks = FastForestClassification.Remarks,
 UserName = FastForestClassification.UserNameValue,
 ShortName = FastForestClassification.ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastForestClassification.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.FastTree/RandomForestRegression.cs

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Expand Up@@ -280,10 +280,10 @@ public BasicImpl(Dataset trainData, Arguments args)

 public static partial class FastForest
 {
 [TlcModule.EntryPoint(Name = "Trainers.FastForestRegressor",
 Desc = FastForestRegression.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FastForestRegressor",
 Desc = FastForestRegression.Summary,
 Remarks = FastForestRegression.Remarks,
 UserName = FastForestRegression.LoadNameValue,
 UserName = FastForestRegression.LoadNameValue,
 ShortName = FastForestRegression.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastForestRegression.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.KMeansClustering/KMeansPlusPlusTrainer.cs

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Expand Up@@ -233,10 +233,10 @@ private static int ComputeNumThreads(IHost host, int? argNumThreads)
 return Math.Max(1, maxThreads);
 }

 [TlcModule.EntryPoint(Name = "Trainers.KMeansPlusPlusClusterer",
 [TlcModule.EntryPoint(Name = "Trainers.KMeansPlusPlusClusterer",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.ClusteringOutput TrainKMeans(IHostEnvironment env, Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.PCA/PcaTrainer.cs

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Expand Up@@ -284,10 +284,10 @@ private static void PostProcess(VBuffer<Float>[] y, Float[] sigma, Float[] z, in
 }
 }

 [TlcModule.EntryPoint(Name = "Trainers.PcaAnomalyDetector",
 [TlcModule.EntryPoint(Name = "Trainers.PcaAnomalyDetector",
 Desc = "Train an PCA Anomaly model.",
 Remarks = PcaPredictor.Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.AnomalyDetectionOutput TrainPcaAnomaly(IHostEnvironment env, Arguments input)
 {
Expand Down

8 changes: 3 additions & 5 deletions
src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineTrainer.cs

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Expand Up@@ -11,9 +11,7 @@
using Microsoft.ML.Runtime.EntryPoints;
using Microsoft.ML.Runtime.FactorizationMachine;
using Microsoft.ML.Runtime.Internal.CpuMath;
using Microsoft.ML.Runtime.Internal.Internallearn;
using Microsoft.ML.Runtime.Internal.Utilities;
using Microsoft.ML.Runtime.Model;
using Microsoft.ML.Runtime.Training;

[assembly: LoadableClass(FieldAwareFactorizationMachineTrainer.Summary, typeof(FieldAwareFactorizationMachineTrainer), typeof(FieldAwareFactorizationMachineTrainer.Arguments),
Expand DownExpand Up@@ -413,10 +411,10 @@ public override FieldAwareFactorizationMachinePredictor CreatePredictor()
 return _pred;
 }

 [TlcModule.EntryPoint(Name = "Trainers.FieldAwareFactorizationMachineBinaryClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.FieldAwareFactorizationMachineBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserName,
 UserName = UserName,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.StandardLearners/Standard/LinearClassificationTrainer.cs

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Expand Up@@ -189,7 +189,7 @@ public abstract class ArgumentsBase : LearnerInputBaseWithLabel
 public int? MaxIterations;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 public bool Shuffle = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Convergence check frequency (in terms of number of iterations). Set as negative or zero for not checking at all. If left blank, it defaults to check after every 'numThreads' iterations.", NullName = "<Auto>", ShortName = "checkFreq")]
Expand DownExpand Up@@ -1507,7 +1507,7 @@ public sealed class Arguments : LearnerInputBaseWithWeight
 public Double InitLearningRate = 0.01;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 [TlcModule.SweepableDiscreteParamAttribute("Shuffle", null, isBool:true)]
 public bool Shuffle = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "Apply weight to the positive class, for imbalanced data", ShortName = "piw")]
Expand DownExpand Up@@ -1795,10 +1795,10 @@ public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironm
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentBinaryClassifier",
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentBinaryClassifier",
 Desc = "Train an SDCA binary model.",
 Remarks = LinearClassificationTrainer.Remarks,
 UserName = LinearClassificationTrainer.UserNameValue,
 UserName = LinearClassificationTrainer.UserNameValue,
 ShortName = LinearClassificationTrainer.LoadNameValue)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, LinearClassificationTrainer.Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LogisticRegression.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -386,10 +386,10 @@ public override ParameterMixingCalibratedPredictor CreatePredictor()
 new PlattCalibrator(Host, -1, 0));
 }

 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionBinaryClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

6 changes: 3 additions & 3 deletions
...Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs

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Expand Up@@ -961,10 +961,10 @@ public IRow GetStatsIRowOrNull(RoleMappedSchema schema)
 /// </summary>
 public partial class LogisticRegression
 {
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionClassifier",
 Desc = Summary,
 [TlcModule.EntryPoint(Name = "Trainers.LogisticRegressionClassifier",
 Desc = Summary,
 Remarks = MulticlassLogisticRegression.Remarks,
 UserName = MulticlassLogisticRegression.UserNameValue,
 UserName = MulticlassLogisticRegression.UserNameValue,
 ShortName = MulticlassLogisticRegression.ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClass(IHostEnvironment env, MulticlassLogisticRegression.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/MultiClass/MultiClassNaiveBayesTrainer.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -130,8 +130,8 @@ public override MultiClassNaiveBayesPredictor CreatePredictor()
 return _predictor;
 }

 [TlcModule.EntryPoint(Name = "Trainers.NaiveBayesClassifier",
 Desc = "Train a MultiClassNaiveBayesTrainer.",
 [TlcModule.EntryPoint(Name = "Trainers.NaiveBayesClassifier",
 Desc = "Train a MultiClassNaiveBayesTrainer.",
 UserName = UserName, ShortName = ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClassNaiveBayesTrainer(IHostEnvironment env, Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/Online/AveragedPerceptron.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -110,10 +110,10 @@ public override LinearBinaryPredictor CreatePredictor()
 return new LinearBinaryPredictor(Host, ref weights, bias);
 }

 [TlcModule.EntryPoint(Name = "Trainers.AveragedPerceptronBinaryClassifier",
 [TlcModule.EntryPoint(Name = "Trainers.AveragedPerceptronBinaryClassifier",
 Desc = Summary,
 Remarks = Remarks,
 UserName = UserNameValue,
 UserName = UserNameValue,
 ShortName = ShortName)]
 public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, Arguments input)
 {
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.StandardLearners/Standard/Online/OnlineGradientDescent.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -94,7 +94,7 @@ public override TPredictor CreatePredictor()
 return new LinearRegressionPredictor(Host, ref weights, bias);
 }

 [TlcModule.EntryPoint(Name = "Trainers.OnlineGradientDescentRegressor",
 [TlcModule.EntryPoint(Name = "Trainers.OnlineGradientDescentRegressor",
 Desc = "Train a Online gradient descent perceptron.",
 Remarks = Remarks,
 UserName = UserNameValue,
Expand Down

2 changes: 1 addition & 1 deletion
src/Microsoft.ML.StandardLearners/Standard/PoissonRegression/PoissonRegression.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -32,7 +32,7 @@ public sealed class PoissonRegression : LbfgsTrainerBase<Float, PoissonRegressio
 internal const string UserNameValue = "Poisson Regression";
 internal const string ShortName = "PR";
 internal const string Summary = "Poisson Regression assumes the unknown function, denoted Y has a Poisson distribution.";
new internal const string Remarks = @"<remarks>
 internal new const string Remarks = @"<remarks>
@zeahmedzeahmedJul 3, 2018

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@Ivanidzo4ka, It has be reverted here as well...:)

I have opened PR (486) to fix it.
<a href='https://en.wikipedia.org/wiki/Poisson_regression'>Poisson regression</a> is a parameterized regression method. 
It assumes that the log of the conditional mean of the dependent variable follows a linear function of the dependent variables. 
Assuming that the dependent variable follows a Poisson distribution, the parameters of the regressor can be estimated by maximizing the likelihood of the obtained observations.
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.StandardLearners/Standard/SdcaMultiClass.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -386,10 +386,10 @@ protected override Float GetInstanceWeight(FloatLabelCursor cursor)
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentClassifier",
 Desc = SdcaMultiClassTrainer.Summary,
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentClassifier",
 Desc = SdcaMultiClassTrainer.Summary,
 Remarks = SdcaMultiClassTrainer.Remarks,
 UserName = SdcaMultiClassTrainer.UserNameValue,
 UserName = SdcaMultiClassTrainer.UserNameValue,
 ShortName = SdcaMultiClassTrainer.ShortName)]
 public static CommonOutputs.MulticlassClassificationOutput TrainMultiClass(IHostEnvironment env, SdcaMultiClassTrainer.Arguments input)
 {
Expand Down

4 changes: 2 additions & 2 deletions
src/Microsoft.ML.StandardLearners/Standard/SdcaRegression.cs

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Expand Up@@ -131,10 +131,10 @@ protected override Float TuneDefaultL2(IChannel ch, int maxIterations, long rowC
 /// </summary>
 public static partial class Sdca
 {
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentRegressor",
 [TlcModule.EntryPoint(Name = "Trainers.StochasticDualCoordinateAscentRegressor",
 Desc = SdcaRegressionTrainer.Summary,
 Remarks = SdcaRegressionTrainer.Remarks,
 UserName = SdcaRegressionTrainer.UserNameValue,
 UserName = SdcaRegressionTrainer.UserNameValue,
 ShortName = SdcaRegressionTrainer.ShortName)]
 public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, SdcaRegressionTrainer.Arguments input)
 {
Expand Down

10 changes: 5 additions & 5 deletions
src/Microsoft.ML.Transforms/BootstrapSampleTransform.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -92,11 +92,11 @@ public BootstrapSampleTransform(IHostEnvironment env, Arguments args, IDataView
 /// <param name="seed">The random seed. If unspecified random state will be instead derived from the environment.</param>
 /// <param name="shuffleInput">Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.</param>
 /// <param name="poolSize">When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.</param>
 public BootstrapSampleTransform(IHostEnvironment env,
 IDataView input,
 bool complement = Defaults.Complement,
 uint? seed = null,
 bool shuffleInput = Defaults.ShuffleInput,
 public BootstrapSampleTransform(IHostEnvironment env,
 IDataView input,
 bool complement = Defaults.Complement,
 uint? seed = null,
 bool shuffleInput = Defaults.ShuffleInput,
 int poolSize = Defaults.PoolSize)
 : this(env, new Arguments() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
 {
Expand Down
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