Fix typo in time series forecasting API.#3944

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codemzs merged 2 commits into from
Jul 1, 2019
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Fix typo in time series forecasting API. #3944

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584ae66
Fix typo in time series forecasting API.
codemzs Jul 1, 2019
327409a
manifest.
codemzs Jul 1, 2019
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4 changes: 2 additions & 2 deletions ...s/Microsoft.ML.Samples/Dynamic/Transforms/TimeSeries/ForecastingWithConfidenceInterval.cs
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Expand Up@@ -48,8 +48,8 @@ public static void Example()
// Instantiate the forecasting model.
var model = ml.Forecasting.ForecastBySsa(outputColumnName, inputColumnName, 5, 11, data.Count, 5,
confidenceLevel: 0.95f,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound");

// Train.
var transformer = model.Fit(dataView);
Expand Down
14 changes: 7 additions & 7 deletions src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs
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Expand Up@@ -164,11 +164,11 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
/// <param name="rank">The desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
/// If set to null, the rank is automatically determined based on prediction error minimization.</param>
/// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
/// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
/// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
/// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
/// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
/// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
/// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
/// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
/// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
/// <param name="confidenceLevel">The confidence level for forecasting.</param>
/// <param name="variableHorizon">Set this to true if horizon will change after training(at prediction time).</param>
/// <example>
Expand All@@ -182,10 +182,10 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
public static SsaForecastingEstimator ForecastBySsa(
this ForecastingCatalog catalog, string outputColumnName, string inputColumnName, int windowSize, int seriesLength, int trainSize, int horizon,
bool isAdaptive = false, float discountFactor = 1, RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact, int? rank = null,
int? maxRank = null, bool shouldStablize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string forcastingConfidentLowerBoundColumnName = null,
string forcastingConfidentUpperBoundColumnName = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
int? maxRank = null, bool shouldStabilize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string lowerBoundConfidenceColumn = null,
string upperBoundConfidenceColumn = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
new SsaForecastingEstimator(CatalogUtils.GetEnvironment(catalog), outputColumnName, inputColumnName, windowSize, seriesLength, trainSize,
horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStablize, shouldMaintainInfo, maxGrowth, forcastingConfidentLowerBoundColumnName,
forcastingConfidentUpperBoundColumnName, confidenceLevel, variableHorizon);
horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStabilize, shouldMaintainInfo, maxGrowth, lowerBoundConfidenceColumn,
upperBoundConfidenceColumn, confidenceLevel, variableHorizon);
}
}
40 changes: 20 additions & 20 deletions src/Microsoft.ML.TimeSeries/SSaForecasting.cs
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Original file line numberDiff line numberDiff line change
Expand Up@@ -42,10 +42,10 @@ internal sealed class Options : TransformInputBase
public string Name;

[Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname", SortOrder = 3)]
public string ForcastingConfidentLowerBoundColumnName;
public string LowerBoundConfidenceColumn;

[Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname", SortOrder = 3)]
public string ForcastingConfidentUpperBoundColumnName;
public string UpperBoundConfidenceColumn;

[Argument(ArgumentType.AtMostOnce, HelpText = "The discount factor in [0,1] used for online updates.", ShortName = "disc", SortOrder = 5)]
public float DiscountFactor = 1;
Expand All@@ -67,7 +67,7 @@ internal sealed class Options : TransformInputBase
public int? MaxRank = null;

[Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the model should be stabilized.", SortOrder = 3)]
public bool ShouldStablize = true;
public bool ShouldStabilize = true;

[Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the meta information for the model needs to be maintained.", SortOrder = 3)]
public bool ShouldMaintainInfo = false;
Expand DownExpand Up@@ -97,14 +97,14 @@ public BaseArguments(Options options)
{
Source = options.Source;
Name = options.Name;
ForcastingConfidentLowerBoundColumnName = options.ForcastingConfidentLowerBoundColumnName;
ForcastingConfidentUpperBoundColumnName = options.ForcastingConfidentUpperBoundColumnName;
LowerBoundConfidenceColumn = options.LowerBoundConfidenceColumn;
UpperBoundConfidenceColumn = options.UpperBoundConfidenceColumn;
WindowSize = options.WindowSize;
DiscountFactor = options.DiscountFactor;
IsAdaptive = options.IsAdaptive;
RankSelectionMethod = options.RankSelectionMethod;
Rank = options.Rank;
ShouldStablize = options.ShouldStablize;
ShouldStablize = options.ShouldStabilize;
MaxGrowth = options.MaxGrowth;
SeriesLength = options.SeriesLength;
TrainSize = options.TrainSize;
Expand DownExpand Up@@ -255,11 +255,11 @@ public sealed class SsaForecastingEstimator : IEstimator<SsaForecastingTransform
/// <param name="rank">The desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
/// If set to null, the rank is automatically determined based on prediction error minimization.</param>
/// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
/// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
/// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
/// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
/// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
/// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
/// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
/// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
/// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
/// <param name="confidenceLevel">The confidence level for forecasting.</param>
/// <param name="variableHorizon">Set this to true if horizon will change after training.</param>
internal SsaForecastingEstimator(IHostEnvironment env,
Expand All@@ -274,11 +274,11 @@ internal SsaForecastingEstimator(IHostEnvironment env,
RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact,
int? rank = null,
int? maxRank = null,
bool shouldStablize = true,
bool shouldStabilize = true,
bool shouldMaintainInfo = false,
GrowthRatio? maxGrowth = null,
string forcastingConfidentLowerBoundColumnName = null,
string forcastingConfidentUpperBoundColumnName = null,
string lowerBoundConfidenceColumn = null,
string upperBoundConfidenceColumn = null,
float confidenceLevel = 0.95f,
bool variableHorizon = false)
: this(env, new SsaForecastingTransformer.Options
Expand All@@ -291,12 +291,12 @@ internal SsaForecastingEstimator(IHostEnvironment env,
RankSelectionMethod = rankSelectionMethod,
Rank = rank,
MaxRank = maxRank,
ShouldStablize = shouldStablize,
ShouldStabilize = shouldStabilize,
ShouldMaintainInfo = shouldMaintainInfo,
MaxGrowth = maxGrowth,
ConfidenceLevel = confidenceLevel,
ForcastingConfidentLowerBoundColumnName = forcastingConfidentLowerBoundColumnName,
ForcastingConfidentUpperBoundColumnName = forcastingConfidentUpperBoundColumnName,
LowerBoundConfidenceColumn = lowerBoundConfidenceColumn,
UpperBoundConfidenceColumn = upperBoundConfidenceColumn,
SeriesLength = seriesLength,
TrainSize = trainSize,
VariableHorizon = variableHorizon,
Expand DownExpand Up@@ -344,14 +344,14 @@ public SchemaShape GetOutputSchema(SchemaShape inputSchema)
resultDic[_options.Name] = new SchemaShape.Column(
_options.Name, SchemaShape.Column.VectorKind.Vector, NumberDataViewType.Single, false);

if (!string.IsNullOrEmpty(_options.ForcastingConfidentUpperBoundColumnName))
if (!string.IsNullOrEmpty(_options.UpperBoundConfidenceColumn))
{
resultDic[_options.ForcastingConfidentLowerBoundColumnName] = new SchemaShape.Column(
_options.ForcastingConfidentLowerBoundColumnName, SchemaShape.Column.VectorKind.Vector,
resultDic[_options.LowerBoundConfidenceColumn] = new SchemaShape.Column(
_options.LowerBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
NumberDataViewType.Single, false);

resultDic[_options.ForcastingConfidentUpperBoundColumnName] = new SchemaShape.Column(
_options.ForcastingConfidentUpperBoundColumnName, SchemaShape.Column.VectorKind.Vector,
resultDic[_options.UpperBoundConfidenceColumn] = new SchemaShape.Column(
_options.UpperBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
NumberDataViewType.Single, false);
}

Expand Down
8 changes: 4 additions & 4 deletions src/Microsoft.ML.TimeSeries/SequentialForecastingTransformBase.cs
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Expand Up@@ -28,11 +28,11 @@ internal abstract class ForecastingArgumentsBase

[Argument(ArgumentType.Required, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname",
SortOrder = 2)]
public string ForcastingConfidentLowerBoundColumnName;
public string LowerBoundConfidenceColumn;

[Argument(ArgumentType.Required, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname",
SortOrder = 2)]
public string ForcastingConfidentUpperBoundColumnName;
public string UpperBoundConfidenceColumn;

[Argument(ArgumentType.AtMostOnce, HelpText = "The length of series from the begining used for training.", ShortName = "wnd",
SortOrder = 3)]
Expand DownExpand Up@@ -67,8 +67,8 @@ private protected SequentialForecastingTransformBase(int windowSize, int initial
}

private protected SequentialForecastingTransformBase(ForecastingArgumentsBase args, string name, int outputLength, IHostEnvironment env)
: this(args.TrainSize, args.SeriesLength, args.Source, args.ForcastingConfidentLowerBoundColumnName,
args.ForcastingConfidentUpperBoundColumnName, args.Name, name, outputLength, env)
: this(args.TrainSize, args.SeriesLength, args.Source, args.LowerBoundConfidenceColumn,
args.UpperBoundConfidenceColumn, args.Name, name, outputLength, env)
{
}

Expand Down
6 changes: 3 additions & 3 deletions src/Microsoft.ML.TimeSeries/SsaForecastingBase.cs
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Expand Up@@ -127,16 +127,16 @@ internal sealed class SsaForecastingBase : SequentialForecastingTransformBase<fl
internal SequenceModelerBase<Single, Single> Model;

public SsaForecastingBase(SsaForecastingOptions options, string name, IHostEnvironment env, SsaForecastingBaseWrapper parent)
: base(options.TrainSize, 0, options.Source, options.Name, options.ForcastingConfidentLowerBoundColumnName,
options.ForcastingConfidentUpperBoundColumnName, name, options.VariableHorizon ? 0: options.Horizon, env)
: base(options.TrainSize, 0, options.Source, options.Name, options.LowerBoundConfidenceColumn,
options.UpperBoundConfidenceColumn, name, options.VariableHorizon ? 0: options.Horizon, env)
{
Host.CheckUserArg(0 <= options.DiscountFactor && options.DiscountFactor <= 1, nameof(options.DiscountFactor), "Must be in the range [0, 1].");
IsAdaptive = options.IsAdaptive;
Horizon = options.Horizon;
ConfidenceLevel = options.ConfidenceLevel;
// Creating the master SSA model
Model = new AdaptiveSingularSpectrumSequenceModelerInternal(Host, options.TrainSize, options.SeriesLength, options.WindowSize,
options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.ForcastingConfidentLowerBoundColumnName),
options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.LowerBoundConfidenceColumn),
options.ShouldStablize, options.ShouldMaintainInfo, options.MaxGrowth);

StateRef = new State();
Expand Down
6 changes: 3 additions & 3 deletions test/BaselineOutput/Common/EntryPoints/core_manifest.json
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Original file line numberDiff line numberDiff line change
Expand Up@@ -4095,7 +4095,7 @@
"Default": false
},
{
"Name": "ForcastingConfidentLowerBoundColumnName",
"Name": "LowerBoundConfidenceColumn",
"Type": "String",
"Desc": "The name of the confidence interval lower bound column.",
"Aliases": [
Expand All@@ -4107,7 +4107,7 @@
"Default": null
},
{
"Name": "ForcastingConfidentUpperBoundColumnName",
"Name": "UpperBoundConfidenceColumn",
"Type": "String",
"Desc": "The name of the confidence interval upper bound column.",
"Aliases": [
Expand DownExpand Up@@ -4153,7 +4153,7 @@
"Default": null
},
{
"Name": "ShouldStablize",
"Name": "ShouldStabilize",
"Type": "Bool",
"Desc": "The flag determining whether the model should be stabilized.",
"Required": false,
Expand Down
12 changes: 6 additions & 6 deletions test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs
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Expand Up@@ -338,8 +338,8 @@ public void SsaForecast()
ConfidenceLevel = 0.95f,
Source = "Value",
Name = "Forecast",
ForcastingConfidentLowerBoundColumnName = "MinCnf",
ForcastingConfidentUpperBoundColumnName = "MaxCnf",
LowerBoundConfidenceColumn = "MinCnf",
UpperBoundConfidenceColumn = "MaxCnf",
WindowSize = 10,
SeriesLength = 11,
TrainSize = 22,
Expand DownExpand Up@@ -397,8 +397,8 @@ public void SsaForecastPredictionEngine()
SeriesLength = 11,
TrainSize = 22,
Horizon = 4,
ForcastingConfidentLowerBoundColumnName = "ConfidenceLowerBound",
ForcastingConfidentUpperBoundColumnName = "ConfidenceUpperBound",
LowerBoundConfidenceColumn = "ConfidenceLowerBound",
UpperBoundConfidenceColumn = "ConfidenceUpperBound",
VariableHorizon = true
};

Expand All@@ -413,8 +413,8 @@ public void SsaForecastPredictionEngine()
var model = ml.Transforms.Text.FeaturizeText("Text_Featurized", "Text")
.Append(ml.Transforms.Conversion.ConvertType("Value", "Value", DataKind.Single))
.Append(ml.Forecasting.ForecastBySsa("Forecast", "Value", 10, 11, 22, 4,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound", variableHorizon: true))
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound", variableHorizon: true))
.Append(ml.Transforms.Concatenate("Forecast", "Forecast", "ConfidenceLowerBound", "ConfidenceUpperBound"))
.Fit(dataView);

Expand Down
4 changes: 2 additions & 2 deletions test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs
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Expand Up@@ -95,8 +95,8 @@ void TestSsaForecastingEstimator()

// Train
var pipe = new SsaForecastingEstimator(Env, "Forecast", "Value", 10, 11, 22, 4,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound");

var xyData = new List<TestDataXY> { new TestDataXY() { A = new float[inputSize] } };
var stringData = new List<TestDataDifferntType> { new TestDataDifferntType() { data_0 = new string[inputSize] } };
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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Fix typo in time series forecasting API.#3944

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 Merged

codemzs
merged 2 commits into

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Jul 1, 2019
 Merged


Fix typo in time series forecasting API.
#3944
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584ae66

Fix typo in time series forecasting API.


codemzs Jul 1, 2019
327409a

manifest.


codemzs Jul 1, 2019

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4 changes: 2 additions & 2 deletions
...s/Microsoft.ML.Samples/Dynamic/Transforms/TimeSeries/ForecastingWithConfidenceInterval.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -48,8 +48,8 @@ public static void Example()
 // Instantiate the forecasting model.
 var model = ml.Forecasting.ForecastBySsa(outputColumnName, inputColumnName, 5, 11, data.Count, 5,
 confidenceLevel: 0.95f,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound");

 // Train.
 var transformer = model.Fit(dataView);
Expand Down

14 changes: 7 additions & 7 deletions
src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -164,11 +164,11 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
 /// <param name="rank">The desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
 /// If set to null, the rank is automatically determined based on prediction error minimization.</param>
 /// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
 /// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
 /// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
 /// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="confidenceLevel">The confidence level for forecasting.</param>
 /// <param name="variableHorizon">Set this to true if horizon will change after training(at prediction time).</param>
 /// <example>
Expand All@@ -182,10 +182,10 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
 public static SsaForecastingEstimator ForecastBySsa(
 this ForecastingCatalog catalog, string outputColumnName, string inputColumnName, int windowSize, int seriesLength, int trainSize, int horizon,
 bool isAdaptive = false, float discountFactor = 1, RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact, int? rank = null,
 int? maxRank = null, bool shouldStablize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string forcastingConfidentLowerBoundColumnName = null,
 string forcastingConfidentUpperBoundColumnName = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
 int? maxRank = null, bool shouldStabilize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string lowerBoundConfidenceColumn = null,
 string upperBoundConfidenceColumn = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
 new SsaForecastingEstimator(CatalogUtils.GetEnvironment(catalog), outputColumnName, inputColumnName, windowSize, seriesLength, trainSize,
 horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStablize, shouldMaintainInfo, maxGrowth, forcastingConfidentLowerBoundColumnName,
forcastingConfidentUpperBoundColumnName, confidenceLevel, variableHorizon);
 horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStabilize, shouldMaintainInfo, maxGrowth, lowerBoundConfidenceColumn,
upperBoundConfidenceColumn, confidenceLevel, variableHorizon);
 }
}

40 changes: 20 additions & 20 deletions
src/Microsoft.ML.TimeSeries/SSaForecasting.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -42,10 +42,10 @@ internal sealed class Options : TransformInputBase
 public string Name;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname", SortOrder = 3)]
 public string ForcastingConfidentLowerBoundColumnName;
 public string LowerBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname", SortOrder = 3)]
 public string ForcastingConfidentUpperBoundColumnName;
 public string UpperBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The discount factor in [0,1] used for online updates.", ShortName = "disc", SortOrder = 5)]
 public float DiscountFactor = 1;
Expand All@@ -67,7 +67,7 @@ internal sealed class Options : TransformInputBase
 public int? MaxRank = null;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the model should be stabilized.", SortOrder = 3)]
 public bool ShouldStablize = true;
 public bool ShouldStabilize = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the meta information for the model needs to be maintained.", SortOrder = 3)]
 public bool ShouldMaintainInfo = false;
Expand DownExpand Up@@ -97,14 +97,14 @@ public BaseArguments(Options options)
 {
 Source = options.Source;
 Name = options.Name;
ForcastingConfidentLowerBoundColumnName = options.ForcastingConfidentLowerBoundColumnName;
ForcastingConfidentUpperBoundColumnName = options.ForcastingConfidentUpperBoundColumnName;
LowerBoundConfidenceColumn = options.LowerBoundConfidenceColumn;
UpperBoundConfidenceColumn = options.UpperBoundConfidenceColumn;
 WindowSize = options.WindowSize;
 DiscountFactor = options.DiscountFactor;
 IsAdaptive = options.IsAdaptive;
 RankSelectionMethod = options.RankSelectionMethod;
 Rank = options.Rank;
 ShouldStablize = options.ShouldStablize;
 ShouldStablize = options.ShouldStabilize;
 MaxGrowth = options.MaxGrowth;
 SeriesLength = options.SeriesLength;
 TrainSize = options.TrainSize;
Expand DownExpand Up@@ -255,11 +255,11 @@ public sealed class SsaForecastingEstimator : IEstimator<SsaForecastingTransform
 /// <param name="rank">The desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
 /// If set to null, the rank is automatically determined based on prediction error minimization.</param>
 /// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
 /// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
 /// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
 /// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="confidenceLevel">The confidence level for forecasting.</param>
 /// <param name="variableHorizon">Set this to true if horizon will change after training.</param>
 internal SsaForecastingEstimator(IHostEnvironment env,
Expand All@@ -274,11 +274,11 @@ internal SsaForecastingEstimator(IHostEnvironment env,
 RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact,
 int? rank = null,
 int? maxRank = null,
 bool shouldStablize = true,
 bool shouldStabilize = true,
 bool shouldMaintainInfo = false,
 GrowthRatio? maxGrowth = null,
 string forcastingConfidentLowerBoundColumnName = null,
 string forcastingConfidentUpperBoundColumnName = null,
 string lowerBoundConfidenceColumn = null,
 string upperBoundConfidenceColumn = null,
 float confidenceLevel = 0.95f,
 bool variableHorizon = false)
 : this(env, new SsaForecastingTransformer.Options
Expand All@@ -291,12 +291,12 @@ internal SsaForecastingEstimator(IHostEnvironment env,
 RankSelectionMethod = rankSelectionMethod,
 Rank = rank,
 MaxRank = maxRank,
ShouldStablize = shouldStablize,
ShouldStabilize = shouldStabilize,
 ShouldMaintainInfo = shouldMaintainInfo,
 MaxGrowth = maxGrowth,
 ConfidenceLevel = confidenceLevel,
ForcastingConfidentLowerBoundColumnName = forcastingConfidentLowerBoundColumnName,
ForcastingConfidentUpperBoundColumnName = forcastingConfidentUpperBoundColumnName,
LowerBoundConfidenceColumn = lowerBoundConfidenceColumn,
UpperBoundConfidenceColumn = upperBoundConfidenceColumn,
 SeriesLength = seriesLength,
 TrainSize = trainSize,
 VariableHorizon = variableHorizon,
Expand DownExpand Up@@ -344,14 +344,14 @@ public SchemaShape GetOutputSchema(SchemaShape inputSchema)
 resultDic[_options.Name] = new SchemaShape.Column(
 _options.Name, SchemaShape.Column.VectorKind.Vector, NumberDataViewType.Single, false);

 if (!string.IsNullOrEmpty(_options.ForcastingConfidentUpperBoundColumnName))
 if (!string.IsNullOrEmpty(_options.UpperBoundConfidenceColumn))
 {
 resultDic[_options.ForcastingConfidentLowerBoundColumnName] = new SchemaShape.Column(
 _options.ForcastingConfidentLowerBoundColumnName, SchemaShape.Column.VectorKind.Vector,
 resultDic[_options.LowerBoundConfidenceColumn] = new SchemaShape.Column(
 _options.LowerBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
 NumberDataViewType.Single, false);

 resultDic[_options.ForcastingConfidentUpperBoundColumnName] = new SchemaShape.Column(
 _options.ForcastingConfidentUpperBoundColumnName, SchemaShape.Column.VectorKind.Vector,
 resultDic[_options.UpperBoundConfidenceColumn] = new SchemaShape.Column(
 _options.UpperBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
 NumberDataViewType.Single, false);
 }

Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.TimeSeries/SequentialForecastingTransformBase.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -28,11 +28,11 @@ internal abstract class ForecastingArgumentsBase

 [Argument(ArgumentType.Required, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname",
 SortOrder = 2)]
 public string ForcastingConfidentLowerBoundColumnName;
 public string LowerBoundConfidenceColumn;

 [Argument(ArgumentType.Required, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname",
 SortOrder = 2)]
 public string ForcastingConfidentUpperBoundColumnName;
 public string UpperBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The length of series from the begining used for training.", ShortName = "wnd",
 SortOrder = 3)]
Expand DownExpand Up@@ -67,8 +67,8 @@ private protected SequentialForecastingTransformBase(int windowSize, int initial
 }

 private protected SequentialForecastingTransformBase(ForecastingArgumentsBase args, string name, int outputLength, IHostEnvironment env)
 : this(args.TrainSize, args.SeriesLength, args.Source, args.ForcastingConfidentLowerBoundColumnName,
 args.ForcastingConfidentUpperBoundColumnName, args.Name, name, outputLength, env)
 : this(args.TrainSize, args.SeriesLength, args.Source, args.LowerBoundConfidenceColumn,
 args.UpperBoundConfidenceColumn, args.Name, name, outputLength, env)
 {
 }

Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.TimeSeries/SsaForecastingBase.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -127,16 +127,16 @@ internal sealed class SsaForecastingBase : SequentialForecastingTransformBase<fl
 internal SequenceModelerBase<Single, Single> Model;

 public SsaForecastingBase(SsaForecastingOptions options, string name, IHostEnvironment env, SsaForecastingBaseWrapper parent)
 : base(options.TrainSize, 0, options.Source, options.Name, options.ForcastingConfidentLowerBoundColumnName,
 options.ForcastingConfidentUpperBoundColumnName, name, options.VariableHorizon ? 0: options.Horizon, env)
 : base(options.TrainSize, 0, options.Source, options.Name, options.LowerBoundConfidenceColumn,
 options.UpperBoundConfidenceColumn, name, options.VariableHorizon ? 0: options.Horizon, env)
 {
 Host.CheckUserArg(0 <= options.DiscountFactor && options.DiscountFactor <= 1, nameof(options.DiscountFactor), "Must be in the range [0, 1].");
 IsAdaptive = options.IsAdaptive;
 Horizon = options.Horizon;
 ConfidenceLevel = options.ConfidenceLevel;
 // Creating the master SSA model
 Model = new AdaptiveSingularSpectrumSequenceModelerInternal(Host, options.TrainSize, options.SeriesLength, options.WindowSize,
 options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.ForcastingConfidentLowerBoundColumnName),
 options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.LowerBoundConfidenceColumn),
 options.ShouldStablize, options.ShouldMaintainInfo, options.MaxGrowth);

 StateRef = new State();
Expand Down

6 changes: 3 additions & 3 deletions
test/BaselineOutput/Common/EntryPoints/core_manifest.json

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Original file line numberDiff line numberDiff line change
Expand Up@@ -4095,7 +4095,7 @@
 "Default": false
 },
 {
 "Name": "ForcastingConfidentLowerBoundColumnName",
 "Name": "LowerBoundConfidenceColumn",
 "Type": "String",
 "Desc": "The name of the confidence interval lower bound column.",
 "Aliases": [
Expand All@@ -4107,7 +4107,7 @@
 "Default": null
 },
 {
 "Name": "ForcastingConfidentUpperBoundColumnName",
 "Name": "UpperBoundConfidenceColumn",
 "Type": "String",
 "Desc": "The name of the confidence interval upper bound column.",
 "Aliases": [
Expand DownExpand Up@@ -4153,7 +4153,7 @@
 "Default": null
 },
 {
 "Name": "ShouldStablize",
 "Name": "ShouldStabilize",
 "Type": "Bool",
 "Desc": "The flag determining whether the model should be stabilized.",
 "Required": false,
Expand Down

12 changes: 6 additions & 6 deletions
test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -338,8 +338,8 @@ public void SsaForecast()
 ConfidenceLevel = 0.95f,
 Source = "Value",
 Name = "Forecast",
ForcastingConfidentLowerBoundColumnName = "MinCnf",
ForcastingConfidentUpperBoundColumnName = "MaxCnf",
LowerBoundConfidenceColumn = "MinCnf",
UpperBoundConfidenceColumn = "MaxCnf",
 WindowSize = 10,
 SeriesLength = 11,
 TrainSize = 22,
Expand DownExpand Up@@ -397,8 +397,8 @@ public void SsaForecastPredictionEngine()
 SeriesLength = 11,
 TrainSize = 22,
 Horizon = 4,
ForcastingConfidentLowerBoundColumnName = "ConfidenceLowerBound",
ForcastingConfidentUpperBoundColumnName = "ConfidenceUpperBound",
LowerBoundConfidenceColumn = "ConfidenceLowerBound",
UpperBoundConfidenceColumn = "ConfidenceUpperBound",
 VariableHorizon = true
 };

Expand All@@ -413,8 +413,8 @@ public void SsaForecastPredictionEngine()
 var model = ml.Transforms.Text.FeaturizeText("Text_Featurized", "Text")
 .Append(ml.Transforms.Conversion.ConvertType("Value", "Value", DataKind.Single))
 .Append(ml.Forecasting.ForecastBySsa("Forecast", "Value", 10, 11, 22, 4,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound", variableHorizon: true))
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound", variableHorizon: true))
 .Append(ml.Transforms.Concatenate("Forecast", "Forecast", "ConfidenceLowerBound", "ConfidenceUpperBound"))
 .Fit(dataView);

Expand Down

4 changes: 2 additions & 2 deletions
test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -95,8 +95,8 @@ void TestSsaForecastingEstimator()

 // Train
 var pipe = new SsaForecastingEstimator(Env, "Forecast", "Value", 10, 11, 22, 4,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound");

 var xyData = new List<TestDataXY> { new TestDataXY() { A = new float[inputSize] } };
 var stringData = new List<TestDataDifferntType> { new TestDataDifferntType() { data_0 = new string[inputSize] } };
Expand Down

, 'i');
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");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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codemzs
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Jul 1, 2019
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Fix typo in time series forecasting API.
#3944
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584ae66

Fix typo in time series forecasting API.


codemzs Jul 1, 2019
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codemzs Jul 1, 2019

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4 changes: 2 additions & 2 deletions
...s/Microsoft.ML.Samples/Dynamic/Transforms/TimeSeries/ForecastingWithConfidenceInterval.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -48,8 +48,8 @@ public static void Example()
 // Instantiate the forecasting model.
 var model = ml.Forecasting.ForecastBySsa(outputColumnName, inputColumnName, 5, 11, data.Count, 5,
 confidenceLevel: 0.95f,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound");

 // Train.
 var transformer = model.Fit(dataView);
Expand Down

14 changes: 7 additions & 7 deletions
src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -164,11 +164,11 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
 /// <param name="rank">The desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
 /// If set to null, the rank is automatically determined based on prediction error minimization.</param>
 /// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
 /// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
 /// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
 /// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="confidenceLevel">The confidence level for forecasting.</param>
 /// <param name="variableHorizon">Set this to true if horizon will change after training(at prediction time).</param>
 /// <example>
Expand All@@ -182,10 +182,10 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
 public static SsaForecastingEstimator ForecastBySsa(
 this ForecastingCatalog catalog, string outputColumnName, string inputColumnName, int windowSize, int seriesLength, int trainSize, int horizon,
 bool isAdaptive = false, float discountFactor = 1, RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact, int? rank = null,
 int? maxRank = null, bool shouldStablize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string forcastingConfidentLowerBoundColumnName = null,
 string forcastingConfidentUpperBoundColumnName = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
 int? maxRank = null, bool shouldStabilize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string lowerBoundConfidenceColumn = null,
 string upperBoundConfidenceColumn = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
 new SsaForecastingEstimator(CatalogUtils.GetEnvironment(catalog), outputColumnName, inputColumnName, windowSize, seriesLength, trainSize,
 horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStablize, shouldMaintainInfo, maxGrowth, forcastingConfidentLowerBoundColumnName,
forcastingConfidentUpperBoundColumnName, confidenceLevel, variableHorizon);
 horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStabilize, shouldMaintainInfo, maxGrowth, lowerBoundConfidenceColumn,
upperBoundConfidenceColumn, confidenceLevel, variableHorizon);
 }
}

40 changes: 20 additions & 20 deletions
src/Microsoft.ML.TimeSeries/SSaForecasting.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -42,10 +42,10 @@ internal sealed class Options : TransformInputBase
 public string Name;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname", SortOrder = 3)]
 public string ForcastingConfidentLowerBoundColumnName;
 public string LowerBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname", SortOrder = 3)]
 public string ForcastingConfidentUpperBoundColumnName;
 public string UpperBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The discount factor in [0,1] used for online updates.", ShortName = "disc", SortOrder = 5)]
 public float DiscountFactor = 1;
Expand All@@ -67,7 +67,7 @@ internal sealed class Options : TransformInputBase
 public int? MaxRank = null;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the model should be stabilized.", SortOrder = 3)]
 public bool ShouldStablize = true;
 public bool ShouldStabilize = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the meta information for the model needs to be maintained.", SortOrder = 3)]
 public bool ShouldMaintainInfo = false;
Expand DownExpand Up@@ -97,14 +97,14 @@ public BaseArguments(Options options)
 {
 Source = options.Source;
 Name = options.Name;
ForcastingConfidentLowerBoundColumnName = options.ForcastingConfidentLowerBoundColumnName;
ForcastingConfidentUpperBoundColumnName = options.ForcastingConfidentUpperBoundColumnName;
LowerBoundConfidenceColumn = options.LowerBoundConfidenceColumn;
UpperBoundConfidenceColumn = options.UpperBoundConfidenceColumn;
 WindowSize = options.WindowSize;
 DiscountFactor = options.DiscountFactor;
 IsAdaptive = options.IsAdaptive;
 RankSelectionMethod = options.RankSelectionMethod;
 Rank = options.Rank;
 ShouldStablize = options.ShouldStablize;
 ShouldStablize = options.ShouldStabilize;
 MaxGrowth = options.MaxGrowth;
 SeriesLength = options.SeriesLength;
 TrainSize = options.TrainSize;
Expand DownExpand Up@@ -255,11 +255,11 @@ public sealed class SsaForecastingEstimator : IEstimator<SsaForecastingTransform
 /// <param name="rank">The desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
 /// If set to null, the rank is automatically determined based on prediction error minimization.</param>
 /// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
 /// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
 /// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
 /// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="confidenceLevel">The confidence level for forecasting.</param>
 /// <param name="variableHorizon">Set this to true if horizon will change after training.</param>
 internal SsaForecastingEstimator(IHostEnvironment env,
Expand All@@ -274,11 +274,11 @@ internal SsaForecastingEstimator(IHostEnvironment env,
 RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact,
 int? rank = null,
 int? maxRank = null,
 bool shouldStablize = true,
 bool shouldStabilize = true,
 bool shouldMaintainInfo = false,
 GrowthRatio? maxGrowth = null,
 string forcastingConfidentLowerBoundColumnName = null,
 string forcastingConfidentUpperBoundColumnName = null,
 string lowerBoundConfidenceColumn = null,
 string upperBoundConfidenceColumn = null,
 float confidenceLevel = 0.95f,
 bool variableHorizon = false)
 : this(env, new SsaForecastingTransformer.Options
Expand All@@ -291,12 +291,12 @@ internal SsaForecastingEstimator(IHostEnvironment env,
 RankSelectionMethod = rankSelectionMethod,
 Rank = rank,
 MaxRank = maxRank,
ShouldStablize = shouldStablize,
ShouldStabilize = shouldStabilize,
 ShouldMaintainInfo = shouldMaintainInfo,
 MaxGrowth = maxGrowth,
 ConfidenceLevel = confidenceLevel,
ForcastingConfidentLowerBoundColumnName = forcastingConfidentLowerBoundColumnName,
ForcastingConfidentUpperBoundColumnName = forcastingConfidentUpperBoundColumnName,
LowerBoundConfidenceColumn = lowerBoundConfidenceColumn,
UpperBoundConfidenceColumn = upperBoundConfidenceColumn,
 SeriesLength = seriesLength,
 TrainSize = trainSize,
 VariableHorizon = variableHorizon,
Expand DownExpand Up@@ -344,14 +344,14 @@ public SchemaShape GetOutputSchema(SchemaShape inputSchema)
 resultDic[_options.Name] = new SchemaShape.Column(
 _options.Name, SchemaShape.Column.VectorKind.Vector, NumberDataViewType.Single, false);

 if (!string.IsNullOrEmpty(_options.ForcastingConfidentUpperBoundColumnName))
 if (!string.IsNullOrEmpty(_options.UpperBoundConfidenceColumn))
 {
 resultDic[_options.ForcastingConfidentLowerBoundColumnName] = new SchemaShape.Column(
 _options.ForcastingConfidentLowerBoundColumnName, SchemaShape.Column.VectorKind.Vector,
 resultDic[_options.LowerBoundConfidenceColumn] = new SchemaShape.Column(
 _options.LowerBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
 NumberDataViewType.Single, false);

 resultDic[_options.ForcastingConfidentUpperBoundColumnName] = new SchemaShape.Column(
 _options.ForcastingConfidentUpperBoundColumnName, SchemaShape.Column.VectorKind.Vector,
 resultDic[_options.UpperBoundConfidenceColumn] = new SchemaShape.Column(
 _options.UpperBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
 NumberDataViewType.Single, false);
 }

Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.TimeSeries/SequentialForecastingTransformBase.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -28,11 +28,11 @@ internal abstract class ForecastingArgumentsBase

 [Argument(ArgumentType.Required, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname",
 SortOrder = 2)]
 public string ForcastingConfidentLowerBoundColumnName;
 public string LowerBoundConfidenceColumn;

 [Argument(ArgumentType.Required, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname",
 SortOrder = 2)]
 public string ForcastingConfidentUpperBoundColumnName;
 public string UpperBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The length of series from the begining used for training.", ShortName = "wnd",
 SortOrder = 3)]
Expand DownExpand Up@@ -67,8 +67,8 @@ private protected SequentialForecastingTransformBase(int windowSize, int initial
 }

 private protected SequentialForecastingTransformBase(ForecastingArgumentsBase args, string name, int outputLength, IHostEnvironment env)
 : this(args.TrainSize, args.SeriesLength, args.Source, args.ForcastingConfidentLowerBoundColumnName,
 args.ForcastingConfidentUpperBoundColumnName, args.Name, name, outputLength, env)
 : this(args.TrainSize, args.SeriesLength, args.Source, args.LowerBoundConfidenceColumn,
 args.UpperBoundConfidenceColumn, args.Name, name, outputLength, env)
 {
 }

Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.TimeSeries/SsaForecastingBase.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -127,16 +127,16 @@ internal sealed class SsaForecastingBase : SequentialForecastingTransformBase<fl
 internal SequenceModelerBase<Single, Single> Model;

 public SsaForecastingBase(SsaForecastingOptions options, string name, IHostEnvironment env, SsaForecastingBaseWrapper parent)
 : base(options.TrainSize, 0, options.Source, options.Name, options.ForcastingConfidentLowerBoundColumnName,
 options.ForcastingConfidentUpperBoundColumnName, name, options.VariableHorizon ? 0: options.Horizon, env)
 : base(options.TrainSize, 0, options.Source, options.Name, options.LowerBoundConfidenceColumn,
 options.UpperBoundConfidenceColumn, name, options.VariableHorizon ? 0: options.Horizon, env)
 {
 Host.CheckUserArg(0 <= options.DiscountFactor && options.DiscountFactor <= 1, nameof(options.DiscountFactor), "Must be in the range [0, 1].");
 IsAdaptive = options.IsAdaptive;
 Horizon = options.Horizon;
 ConfidenceLevel = options.ConfidenceLevel;
 // Creating the master SSA model
 Model = new AdaptiveSingularSpectrumSequenceModelerInternal(Host, options.TrainSize, options.SeriesLength, options.WindowSize,
 options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.ForcastingConfidentLowerBoundColumnName),
 options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.LowerBoundConfidenceColumn),
 options.ShouldStablize, options.ShouldMaintainInfo, options.MaxGrowth);

 StateRef = new State();
Expand Down

6 changes: 3 additions & 3 deletions
test/BaselineOutput/Common/EntryPoints/core_manifest.json

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Original file line numberDiff line numberDiff line change
Expand Up@@ -4095,7 +4095,7 @@
 "Default": false
 },
 {
 "Name": "ForcastingConfidentLowerBoundColumnName",
 "Name": "LowerBoundConfidenceColumn",
 "Type": "String",
 "Desc": "The name of the confidence interval lower bound column.",
 "Aliases": [
Expand All@@ -4107,7 +4107,7 @@
 "Default": null
 },
 {
 "Name": "ForcastingConfidentUpperBoundColumnName",
 "Name": "UpperBoundConfidenceColumn",
 "Type": "String",
 "Desc": "The name of the confidence interval upper bound column.",
 "Aliases": [
Expand DownExpand Up@@ -4153,7 +4153,7 @@
 "Default": null
 },
 {
 "Name": "ShouldStablize",
 "Name": "ShouldStabilize",
 "Type": "Bool",
 "Desc": "The flag determining whether the model should be stabilized.",
 "Required": false,
Expand Down

12 changes: 6 additions & 6 deletions
test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -338,8 +338,8 @@ public void SsaForecast()
 ConfidenceLevel = 0.95f,
 Source = "Value",
 Name = "Forecast",
ForcastingConfidentLowerBoundColumnName = "MinCnf",
ForcastingConfidentUpperBoundColumnName = "MaxCnf",
LowerBoundConfidenceColumn = "MinCnf",
UpperBoundConfidenceColumn = "MaxCnf",
 WindowSize = 10,
 SeriesLength = 11,
 TrainSize = 22,
Expand DownExpand Up@@ -397,8 +397,8 @@ public void SsaForecastPredictionEngine()
 SeriesLength = 11,
 TrainSize = 22,
 Horizon = 4,
ForcastingConfidentLowerBoundColumnName = "ConfidenceLowerBound",
ForcastingConfidentUpperBoundColumnName = "ConfidenceUpperBound",
LowerBoundConfidenceColumn = "ConfidenceLowerBound",
UpperBoundConfidenceColumn = "ConfidenceUpperBound",
 VariableHorizon = true
 };

Expand All@@ -413,8 +413,8 @@ public void SsaForecastPredictionEngine()
 var model = ml.Transforms.Text.FeaturizeText("Text_Featurized", "Text")
 .Append(ml.Transforms.Conversion.ConvertType("Value", "Value", DataKind.Single))
 .Append(ml.Forecasting.ForecastBySsa("Forecast", "Value", 10, 11, 22, 4,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound", variableHorizon: true))
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound", variableHorizon: true))
 .Append(ml.Transforms.Concatenate("Forecast", "Forecast", "ConfidenceLowerBound", "ConfidenceUpperBound"))
 .Fit(dataView);

Expand Down

4 changes: 2 additions & 2 deletions
test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -95,8 +95,8 @@ void TestSsaForecastingEstimator()

 // Train
 var pipe = new SsaForecastingEstimator(Env, "Forecast", "Value", 10, 11, 22, 4,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound");

 var xyData = new List<TestDataXY> { new TestDataXY() { A = new float[inputSize] } };
 var stringData = new List<TestDataDifferntType> { new TestDataDifferntType() { data_0 = new string[inputSize] } };
Expand Down

, '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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Fix typo in time series forecasting API.#3944

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Fix typo in time series forecasting API.
#3944
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584ae66

Fix typo in time series forecasting API.


codemzs Jul 1, 2019
327409a

manifest.


codemzs Jul 1, 2019

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4 changes: 2 additions & 2 deletions
...s/Microsoft.ML.Samples/Dynamic/Transforms/TimeSeries/ForecastingWithConfidenceInterval.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -48,8 +48,8 @@ public static void Example()
 // Instantiate the forecasting model.
 var model = ml.Forecasting.ForecastBySsa(outputColumnName, inputColumnName, 5, 11, data.Count, 5,
 confidenceLevel: 0.95f,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound");

 // Train.
 var transformer = model.Fit(dataView);
Expand Down

14 changes: 7 additions & 7 deletions
src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -164,11 +164,11 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
 /// <param name="rank">The desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
 /// If set to null, the rank is automatically determined based on prediction error minimization.</param>
 /// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
 /// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
 /// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
 /// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="confidenceLevel">The confidence level for forecasting.</param>
 /// <param name="variableHorizon">Set this to true if horizon will change after training(at prediction time).</param>
 /// <example>
Expand All@@ -182,10 +182,10 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
 public static SsaForecastingEstimator ForecastBySsa(
 this ForecastingCatalog catalog, string outputColumnName, string inputColumnName, int windowSize, int seriesLength, int trainSize, int horizon,
 bool isAdaptive = false, float discountFactor = 1, RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact, int? rank = null,
 int? maxRank = null, bool shouldStablize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string forcastingConfidentLowerBoundColumnName = null,
 string forcastingConfidentUpperBoundColumnName = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
 int? maxRank = null, bool shouldStabilize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string lowerBoundConfidenceColumn = null,
 string upperBoundConfidenceColumn = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
 new SsaForecastingEstimator(CatalogUtils.GetEnvironment(catalog), outputColumnName, inputColumnName, windowSize, seriesLength, trainSize,
 horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStablize, shouldMaintainInfo, maxGrowth, forcastingConfidentLowerBoundColumnName,
forcastingConfidentUpperBoundColumnName, confidenceLevel, variableHorizon);
 horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStabilize, shouldMaintainInfo, maxGrowth, lowerBoundConfidenceColumn,
upperBoundConfidenceColumn, confidenceLevel, variableHorizon);
 }
}

40 changes: 20 additions & 20 deletions
src/Microsoft.ML.TimeSeries/SSaForecasting.cs

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -42,10 +42,10 @@ internal sealed class Options : TransformInputBase
 public string Name;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname", SortOrder = 3)]
 public string ForcastingConfidentLowerBoundColumnName;
 public string LowerBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname", SortOrder = 3)]
 public string ForcastingConfidentUpperBoundColumnName;
 public string UpperBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The discount factor in [0,1] used for online updates.", ShortName = "disc", SortOrder = 5)]
 public float DiscountFactor = 1;
Expand All@@ -67,7 +67,7 @@ internal sealed class Options : TransformInputBase
 public int? MaxRank = null;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the model should be stabilized.", SortOrder = 3)]
 public bool ShouldStablize = true;
 public bool ShouldStabilize = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the meta information for the model needs to be maintained.", SortOrder = 3)]
 public bool ShouldMaintainInfo = false;
Expand DownExpand Up@@ -97,14 +97,14 @@ public BaseArguments(Options options)
 {
 Source = options.Source;
 Name = options.Name;
ForcastingConfidentLowerBoundColumnName = options.ForcastingConfidentLowerBoundColumnName;
ForcastingConfidentUpperBoundColumnName = options.ForcastingConfidentUpperBoundColumnName;
LowerBoundConfidenceColumn = options.LowerBoundConfidenceColumn;
UpperBoundConfidenceColumn = options.UpperBoundConfidenceColumn;
 WindowSize = options.WindowSize;
 DiscountFactor = options.DiscountFactor;
 IsAdaptive = options.IsAdaptive;
 RankSelectionMethod = options.RankSelectionMethod;
 Rank = options.Rank;
 ShouldStablize = options.ShouldStablize;
 ShouldStablize = options.ShouldStabilize;
 MaxGrowth = options.MaxGrowth;
 SeriesLength = options.SeriesLength;
 TrainSize = options.TrainSize;
Expand DownExpand Up@@ -255,11 +255,11 @@ public sealed class SsaForecastingEstimator : IEstimator<SsaForecastingTransform
 /// <param name="rank">The desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
 /// If set to null, the rank is automatically determined based on prediction error minimization.</param>
 /// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
 /// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
 /// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
 /// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="confidenceLevel">The confidence level for forecasting.</param>
 /// <param name="variableHorizon">Set this to true if horizon will change after training.</param>
 internal SsaForecastingEstimator(IHostEnvironment env,
Expand All@@ -274,11 +274,11 @@ internal SsaForecastingEstimator(IHostEnvironment env,
 RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact,
 int? rank = null,
 int? maxRank = null,
 bool shouldStablize = true,
 bool shouldStabilize = true,
 bool shouldMaintainInfo = false,
 GrowthRatio? maxGrowth = null,
 string forcastingConfidentLowerBoundColumnName = null,
 string forcastingConfidentUpperBoundColumnName = null,
 string lowerBoundConfidenceColumn = null,
 string upperBoundConfidenceColumn = null,
 float confidenceLevel = 0.95f,
 bool variableHorizon = false)
 : this(env, new SsaForecastingTransformer.Options
Expand All@@ -291,12 +291,12 @@ internal SsaForecastingEstimator(IHostEnvironment env,
 RankSelectionMethod = rankSelectionMethod,
 Rank = rank,
 MaxRank = maxRank,
ShouldStablize = shouldStablize,
ShouldStabilize = shouldStabilize,
 ShouldMaintainInfo = shouldMaintainInfo,
 MaxGrowth = maxGrowth,
 ConfidenceLevel = confidenceLevel,
ForcastingConfidentLowerBoundColumnName = forcastingConfidentLowerBoundColumnName,
ForcastingConfidentUpperBoundColumnName = forcastingConfidentUpperBoundColumnName,
LowerBoundConfidenceColumn = lowerBoundConfidenceColumn,
UpperBoundConfidenceColumn = upperBoundConfidenceColumn,
 SeriesLength = seriesLength,
 TrainSize = trainSize,
 VariableHorizon = variableHorizon,
Expand DownExpand Up@@ -344,14 +344,14 @@ public SchemaShape GetOutputSchema(SchemaShape inputSchema)
 resultDic[_options.Name] = new SchemaShape.Column(
 _options.Name, SchemaShape.Column.VectorKind.Vector, NumberDataViewType.Single, false);

 if (!string.IsNullOrEmpty(_options.ForcastingConfidentUpperBoundColumnName))
 if (!string.IsNullOrEmpty(_options.UpperBoundConfidenceColumn))
 {
 resultDic[_options.ForcastingConfidentLowerBoundColumnName] = new SchemaShape.Column(
 _options.ForcastingConfidentLowerBoundColumnName, SchemaShape.Column.VectorKind.Vector,
 resultDic[_options.LowerBoundConfidenceColumn] = new SchemaShape.Column(
 _options.LowerBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
 NumberDataViewType.Single, false);

 resultDic[_options.ForcastingConfidentUpperBoundColumnName] = new SchemaShape.Column(
 _options.ForcastingConfidentUpperBoundColumnName, SchemaShape.Column.VectorKind.Vector,
 resultDic[_options.UpperBoundConfidenceColumn] = new SchemaShape.Column(
 _options.UpperBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
 NumberDataViewType.Single, false);
 }

Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.TimeSeries/SequentialForecastingTransformBase.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -28,11 +28,11 @@ internal abstract class ForecastingArgumentsBase

 [Argument(ArgumentType.Required, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname",
 SortOrder = 2)]
 public string ForcastingConfidentLowerBoundColumnName;
 public string LowerBoundConfidenceColumn;

 [Argument(ArgumentType.Required, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname",
 SortOrder = 2)]
 public string ForcastingConfidentUpperBoundColumnName;
 public string UpperBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The length of series from the begining used for training.", ShortName = "wnd",
 SortOrder = 3)]
Expand DownExpand Up@@ -67,8 +67,8 @@ private protected SequentialForecastingTransformBase(int windowSize, int initial
 }

 private protected SequentialForecastingTransformBase(ForecastingArgumentsBase args, string name, int outputLength, IHostEnvironment env)
 : this(args.TrainSize, args.SeriesLength, args.Source, args.ForcastingConfidentLowerBoundColumnName,
 args.ForcastingConfidentUpperBoundColumnName, args.Name, name, outputLength, env)
 : this(args.TrainSize, args.SeriesLength, args.Source, args.LowerBoundConfidenceColumn,
 args.UpperBoundConfidenceColumn, args.Name, name, outputLength, env)
 {
 }

Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.TimeSeries/SsaForecastingBase.cs

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -127,16 +127,16 @@ internal sealed class SsaForecastingBase : SequentialForecastingTransformBase<fl
 internal SequenceModelerBase<Single, Single> Model;

 public SsaForecastingBase(SsaForecastingOptions options, string name, IHostEnvironment env, SsaForecastingBaseWrapper parent)
 : base(options.TrainSize, 0, options.Source, options.Name, options.ForcastingConfidentLowerBoundColumnName,
 options.ForcastingConfidentUpperBoundColumnName, name, options.VariableHorizon ? 0: options.Horizon, env)
 : base(options.TrainSize, 0, options.Source, options.Name, options.LowerBoundConfidenceColumn,
 options.UpperBoundConfidenceColumn, name, options.VariableHorizon ? 0: options.Horizon, env)
 {
 Host.CheckUserArg(0 <= options.DiscountFactor && options.DiscountFactor <= 1, nameof(options.DiscountFactor), "Must be in the range [0, 1].");
 IsAdaptive = options.IsAdaptive;
 Horizon = options.Horizon;
 ConfidenceLevel = options.ConfidenceLevel;
 // Creating the master SSA model
 Model = new AdaptiveSingularSpectrumSequenceModelerInternal(Host, options.TrainSize, options.SeriesLength, options.WindowSize,
 options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.ForcastingConfidentLowerBoundColumnName),
 options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.LowerBoundConfidenceColumn),
 options.ShouldStablize, options.ShouldMaintainInfo, options.MaxGrowth);

 StateRef = new State();
Expand Down

6 changes: 3 additions & 3 deletions
test/BaselineOutput/Common/EntryPoints/core_manifest.json

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -4095,7 +4095,7 @@
 "Default": false
 },
 {
 "Name": "ForcastingConfidentLowerBoundColumnName",
 "Name": "LowerBoundConfidenceColumn",
 "Type": "String",
 "Desc": "The name of the confidence interval lower bound column.",
 "Aliases": [
Expand All@@ -4107,7 +4107,7 @@
 "Default": null
 },
 {
 "Name": "ForcastingConfidentUpperBoundColumnName",
 "Name": "UpperBoundConfidenceColumn",
 "Type": "String",
 "Desc": "The name of the confidence interval upper bound column.",
 "Aliases": [
Expand DownExpand Up@@ -4153,7 +4153,7 @@
 "Default": null
 },
 {
 "Name": "ShouldStablize",
 "Name": "ShouldStabilize",
 "Type": "Bool",
 "Desc": "The flag determining whether the model should be stabilized.",
 "Required": false,
Expand Down

12 changes: 6 additions & 6 deletions
test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -338,8 +338,8 @@ public void SsaForecast()
 ConfidenceLevel = 0.95f,
 Source = "Value",
 Name = "Forecast",
ForcastingConfidentLowerBoundColumnName = "MinCnf",
ForcastingConfidentUpperBoundColumnName = "MaxCnf",
LowerBoundConfidenceColumn = "MinCnf",
UpperBoundConfidenceColumn = "MaxCnf",
 WindowSize = 10,
 SeriesLength = 11,
 TrainSize = 22,
Expand DownExpand Up@@ -397,8 +397,8 @@ public void SsaForecastPredictionEngine()
 SeriesLength = 11,
 TrainSize = 22,
 Horizon = 4,
ForcastingConfidentLowerBoundColumnName = "ConfidenceLowerBound",
ForcastingConfidentUpperBoundColumnName = "ConfidenceUpperBound",
LowerBoundConfidenceColumn = "ConfidenceLowerBound",
UpperBoundConfidenceColumn = "ConfidenceUpperBound",
 VariableHorizon = true
 };

Expand All@@ -413,8 +413,8 @@ public void SsaForecastPredictionEngine()
 var model = ml.Transforms.Text.FeaturizeText("Text_Featurized", "Text")
 .Append(ml.Transforms.Conversion.ConvertType("Value", "Value", DataKind.Single))
 .Append(ml.Forecasting.ForecastBySsa("Forecast", "Value", 10, 11, 22, 4,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound", variableHorizon: true))
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound", variableHorizon: true))
 .Append(ml.Transforms.Concatenate("Forecast", "Forecast", "ConfidenceLowerBound", "ConfidenceUpperBound"))
 .Fit(dataView);

Expand Down

4 changes: 2 additions & 2 deletions
test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -95,8 +95,8 @@ void TestSsaForecastingEstimator()

 // Train
 var pipe = new SsaForecastingEstimator(Env, "Forecast", "Value", 10, 11, 22, 4,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound");

 var xyData = new List<TestDataXY> { new TestDataXY() { A = new float[inputSize] } };
 var stringData = new List<TestDataDifferntType> { new TestDataDifferntType() { data_0 = new string[inputSize] } };
Expand Down

, '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" + '

Skip to content
Fix typo in time series forecasting API.#3944

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 Merged

codemzs
merged 2 commits into

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Jul 1, 2019
 Merged


Fix typo in time series forecasting API.
#3944
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584ae66

Fix typo in time series forecasting API.


codemzs Jul 1, 2019
327409a

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codemzs Jul 1, 2019

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4 changes: 2 additions & 2 deletions
...s/Microsoft.ML.Samples/Dynamic/Transforms/TimeSeries/ForecastingWithConfidenceInterval.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -48,8 +48,8 @@ public static void Example()
 // Instantiate the forecasting model.
 var model = ml.Forecasting.ForecastBySsa(outputColumnName, inputColumnName, 5, 11, data.Count, 5,
 confidenceLevel: 0.95f,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound");

 // Train.
 var transformer = model.Fit(dataView);
Expand Down

14 changes: 7 additions & 7 deletions
src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -164,11 +164,11 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
 /// <param name="rank">The desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
 /// If set to null, the rank is automatically determined based on prediction error minimization.</param>
 /// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
 /// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
 /// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
 /// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="confidenceLevel">The confidence level for forecasting.</param>
 /// <param name="variableHorizon">Set this to true if horizon will change after training(at prediction time).</param>
 /// <example>
Expand All@@ -182,10 +182,10 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
 public static SsaForecastingEstimator ForecastBySsa(
 this ForecastingCatalog catalog, string outputColumnName, string inputColumnName, int windowSize, int seriesLength, int trainSize, int horizon,
 bool isAdaptive = false, float discountFactor = 1, RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact, int? rank = null,
 int? maxRank = null, bool shouldStablize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string forcastingConfidentLowerBoundColumnName = null,
 string forcastingConfidentUpperBoundColumnName = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
 int? maxRank = null, bool shouldStabilize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string lowerBoundConfidenceColumn = null,
 string upperBoundConfidenceColumn = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
 new SsaForecastingEstimator(CatalogUtils.GetEnvironment(catalog), outputColumnName, inputColumnName, windowSize, seriesLength, trainSize,
 horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStablize, shouldMaintainInfo, maxGrowth, forcastingConfidentLowerBoundColumnName,
forcastingConfidentUpperBoundColumnName, confidenceLevel, variableHorizon);
 horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStabilize, shouldMaintainInfo, maxGrowth, lowerBoundConfidenceColumn,
upperBoundConfidenceColumn, confidenceLevel, variableHorizon);
 }
}

40 changes: 20 additions & 20 deletions
src/Microsoft.ML.TimeSeries/SSaForecasting.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -42,10 +42,10 @@ internal sealed class Options : TransformInputBase
 public string Name;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname", SortOrder = 3)]
 public string ForcastingConfidentLowerBoundColumnName;
 public string LowerBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname", SortOrder = 3)]
 public string ForcastingConfidentUpperBoundColumnName;
 public string UpperBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The discount factor in [0,1] used for online updates.", ShortName = "disc", SortOrder = 5)]
 public float DiscountFactor = 1;
Expand All@@ -67,7 +67,7 @@ internal sealed class Options : TransformInputBase
 public int? MaxRank = null;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the model should be stabilized.", SortOrder = 3)]
 public bool ShouldStablize = true;
 public bool ShouldStabilize = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the meta information for the model needs to be maintained.", SortOrder = 3)]
 public bool ShouldMaintainInfo = false;
Expand DownExpand Up@@ -97,14 +97,14 @@ public BaseArguments(Options options)
 {
 Source = options.Source;
 Name = options.Name;
ForcastingConfidentLowerBoundColumnName = options.ForcastingConfidentLowerBoundColumnName;
ForcastingConfidentUpperBoundColumnName = options.ForcastingConfidentUpperBoundColumnName;
LowerBoundConfidenceColumn = options.LowerBoundConfidenceColumn;
UpperBoundConfidenceColumn = options.UpperBoundConfidenceColumn;
 WindowSize = options.WindowSize;
 DiscountFactor = options.DiscountFactor;
 IsAdaptive = options.IsAdaptive;
 RankSelectionMethod = options.RankSelectionMethod;
 Rank = options.Rank;
 ShouldStablize = options.ShouldStablize;
 ShouldStablize = options.ShouldStabilize;
 MaxGrowth = options.MaxGrowth;
 SeriesLength = options.SeriesLength;
 TrainSize = options.TrainSize;
Expand DownExpand Up@@ -255,11 +255,11 @@ public sealed class SsaForecastingEstimator : IEstimator<SsaForecastingTransform
 /// <param name="rank">The desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
 /// If set to null, the rank is automatically determined based on prediction error minimization.</param>
 /// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
 /// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
 /// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
 /// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="confidenceLevel">The confidence level for forecasting.</param>
 /// <param name="variableHorizon">Set this to true if horizon will change after training.</param>
 internal SsaForecastingEstimator(IHostEnvironment env,
Expand All@@ -274,11 +274,11 @@ internal SsaForecastingEstimator(IHostEnvironment env,
 RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact,
 int? rank = null,
 int? maxRank = null,
 bool shouldStablize = true,
 bool shouldStabilize = true,
 bool shouldMaintainInfo = false,
 GrowthRatio? maxGrowth = null,
 string forcastingConfidentLowerBoundColumnName = null,
 string forcastingConfidentUpperBoundColumnName = null,
 string lowerBoundConfidenceColumn = null,
 string upperBoundConfidenceColumn = null,
 float confidenceLevel = 0.95f,
 bool variableHorizon = false)
 : this(env, new SsaForecastingTransformer.Options
Expand All@@ -291,12 +291,12 @@ internal SsaForecastingEstimator(IHostEnvironment env,
 RankSelectionMethod = rankSelectionMethod,
 Rank = rank,
 MaxRank = maxRank,
ShouldStablize = shouldStablize,
ShouldStabilize = shouldStabilize,
 ShouldMaintainInfo = shouldMaintainInfo,
 MaxGrowth = maxGrowth,
 ConfidenceLevel = confidenceLevel,
ForcastingConfidentLowerBoundColumnName = forcastingConfidentLowerBoundColumnName,
ForcastingConfidentUpperBoundColumnName = forcastingConfidentUpperBoundColumnName,
LowerBoundConfidenceColumn = lowerBoundConfidenceColumn,
UpperBoundConfidenceColumn = upperBoundConfidenceColumn,
 SeriesLength = seriesLength,
 TrainSize = trainSize,
 VariableHorizon = variableHorizon,
Expand DownExpand Up@@ -344,14 +344,14 @@ public SchemaShape GetOutputSchema(SchemaShape inputSchema)
 resultDic[_options.Name] = new SchemaShape.Column(
 _options.Name, SchemaShape.Column.VectorKind.Vector, NumberDataViewType.Single, false);

 if (!string.IsNullOrEmpty(_options.ForcastingConfidentUpperBoundColumnName))
 if (!string.IsNullOrEmpty(_options.UpperBoundConfidenceColumn))
 {
 resultDic[_options.ForcastingConfidentLowerBoundColumnName] = new SchemaShape.Column(
 _options.ForcastingConfidentLowerBoundColumnName, SchemaShape.Column.VectorKind.Vector,
 resultDic[_options.LowerBoundConfidenceColumn] = new SchemaShape.Column(
 _options.LowerBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
 NumberDataViewType.Single, false);

 resultDic[_options.ForcastingConfidentUpperBoundColumnName] = new SchemaShape.Column(
 _options.ForcastingConfidentUpperBoundColumnName, SchemaShape.Column.VectorKind.Vector,
 resultDic[_options.UpperBoundConfidenceColumn] = new SchemaShape.Column(
 _options.UpperBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
 NumberDataViewType.Single, false);
 }

Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.TimeSeries/SequentialForecastingTransformBase.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -28,11 +28,11 @@ internal abstract class ForecastingArgumentsBase

 [Argument(ArgumentType.Required, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname",
 SortOrder = 2)]
 public string ForcastingConfidentLowerBoundColumnName;
 public string LowerBoundConfidenceColumn;

 [Argument(ArgumentType.Required, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname",
 SortOrder = 2)]
 public string ForcastingConfidentUpperBoundColumnName;
 public string UpperBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The length of series from the begining used for training.", ShortName = "wnd",
 SortOrder = 3)]
Expand DownExpand Up@@ -67,8 +67,8 @@ private protected SequentialForecastingTransformBase(int windowSize, int initial
 }

 private protected SequentialForecastingTransformBase(ForecastingArgumentsBase args, string name, int outputLength, IHostEnvironment env)
 : this(args.TrainSize, args.SeriesLength, args.Source, args.ForcastingConfidentLowerBoundColumnName,
 args.ForcastingConfidentUpperBoundColumnName, args.Name, name, outputLength, env)
 : this(args.TrainSize, args.SeriesLength, args.Source, args.LowerBoundConfidenceColumn,
 args.UpperBoundConfidenceColumn, args.Name, name, outputLength, env)
 {
 }

Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.TimeSeries/SsaForecastingBase.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -127,16 +127,16 @@ internal sealed class SsaForecastingBase : SequentialForecastingTransformBase<fl
 internal SequenceModelerBase<Single, Single> Model;

 public SsaForecastingBase(SsaForecastingOptions options, string name, IHostEnvironment env, SsaForecastingBaseWrapper parent)
 : base(options.TrainSize, 0, options.Source, options.Name, options.ForcastingConfidentLowerBoundColumnName,
 options.ForcastingConfidentUpperBoundColumnName, name, options.VariableHorizon ? 0: options.Horizon, env)
 : base(options.TrainSize, 0, options.Source, options.Name, options.LowerBoundConfidenceColumn,
 options.UpperBoundConfidenceColumn, name, options.VariableHorizon ? 0: options.Horizon, env)
 {
 Host.CheckUserArg(0 <= options.DiscountFactor && options.DiscountFactor <= 1, nameof(options.DiscountFactor), "Must be in the range [0, 1].");
 IsAdaptive = options.IsAdaptive;
 Horizon = options.Horizon;
 ConfidenceLevel = options.ConfidenceLevel;
 // Creating the master SSA model
 Model = new AdaptiveSingularSpectrumSequenceModelerInternal(Host, options.TrainSize, options.SeriesLength, options.WindowSize,
 options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.ForcastingConfidentLowerBoundColumnName),
 options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.LowerBoundConfidenceColumn),
 options.ShouldStablize, options.ShouldMaintainInfo, options.MaxGrowth);

 StateRef = new State();
Expand Down

6 changes: 3 additions & 3 deletions
test/BaselineOutput/Common/EntryPoints/core_manifest.json

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Original file line numberDiff line numberDiff line change
Expand Up@@ -4095,7 +4095,7 @@
 "Default": false
 },
 {
 "Name": "ForcastingConfidentLowerBoundColumnName",
 "Name": "LowerBoundConfidenceColumn",
 "Type": "String",
 "Desc": "The name of the confidence interval lower bound column.",
 "Aliases": [
Expand All@@ -4107,7 +4107,7 @@
 "Default": null
 },
 {
 "Name": "ForcastingConfidentUpperBoundColumnName",
 "Name": "UpperBoundConfidenceColumn",
 "Type": "String",
 "Desc": "The name of the confidence interval upper bound column.",
 "Aliases": [
Expand DownExpand Up@@ -4153,7 +4153,7 @@
 "Default": null
 },
 {
 "Name": "ShouldStablize",
 "Name": "ShouldStabilize",
 "Type": "Bool",
 "Desc": "The flag determining whether the model should be stabilized.",
 "Required": false,
Expand Down

12 changes: 6 additions & 6 deletions
test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -338,8 +338,8 @@ public void SsaForecast()
 ConfidenceLevel = 0.95f,
 Source = "Value",
 Name = "Forecast",
ForcastingConfidentLowerBoundColumnName = "MinCnf",
ForcastingConfidentUpperBoundColumnName = "MaxCnf",
LowerBoundConfidenceColumn = "MinCnf",
UpperBoundConfidenceColumn = "MaxCnf",
 WindowSize = 10,
 SeriesLength = 11,
 TrainSize = 22,
Expand DownExpand Up@@ -397,8 +397,8 @@ public void SsaForecastPredictionEngine()
 SeriesLength = 11,
 TrainSize = 22,
 Horizon = 4,
ForcastingConfidentLowerBoundColumnName = "ConfidenceLowerBound",
ForcastingConfidentUpperBoundColumnName = "ConfidenceUpperBound",
LowerBoundConfidenceColumn = "ConfidenceLowerBound",
UpperBoundConfidenceColumn = "ConfidenceUpperBound",
 VariableHorizon = true
 };

Expand All@@ -413,8 +413,8 @@ public void SsaForecastPredictionEngine()
 var model = ml.Transforms.Text.FeaturizeText("Text_Featurized", "Text")
 .Append(ml.Transforms.Conversion.ConvertType("Value", "Value", DataKind.Single))
 .Append(ml.Forecasting.ForecastBySsa("Forecast", "Value", 10, 11, 22, 4,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound", variableHorizon: true))
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound", variableHorizon: true))
 .Append(ml.Transforms.Concatenate("Forecast", "Forecast", "ConfidenceLowerBound", "ConfidenceUpperBound"))
 .Fit(dataView);

Expand Down

4 changes: 2 additions & 2 deletions
test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -95,8 +95,8 @@ void TestSsaForecastingEstimator()

 // Train
 var pipe = new SsaForecastingEstimator(Env, "Forecast", "Value", 10, 11, 22, 4,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound");

 var xyData = new List<TestDataXY> { new TestDataXY() { A = new float[inputSize] } };
 var stringData = new List<TestDataDifferntType> { new TestDataDifferntType() { data_0 = new string[inputSize] } };
Expand Down

, '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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codemzs
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Jul 1, 2019
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Fix typo in time series forecasting API.
#3944
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584ae66

Fix typo in time series forecasting API.


codemzs Jul 1, 2019
327409a

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codemzs Jul 1, 2019

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4 changes: 2 additions & 2 deletions
...s/Microsoft.ML.Samples/Dynamic/Transforms/TimeSeries/ForecastingWithConfidenceInterval.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -48,8 +48,8 @@ public static void Example()
 // Instantiate the forecasting model.
 var model = ml.Forecasting.ForecastBySsa(outputColumnName, inputColumnName, 5, 11, data.Count, 5,
 confidenceLevel: 0.95f,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound");

 // Train.
 var transformer = model.Fit(dataView);
Expand Down

14 changes: 7 additions & 7 deletions
src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -164,11 +164,11 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
 /// <param name="rank">The desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
 /// If set to null, the rank is automatically determined based on prediction error minimization.</param>
 /// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
 /// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
 /// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
 /// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="confidenceLevel">The confidence level for forecasting.</param>
 /// <param name="variableHorizon">Set this to true if horizon will change after training(at prediction time).</param>
 /// <example>
Expand All@@ -182,10 +182,10 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
 public static SsaForecastingEstimator ForecastBySsa(
 this ForecastingCatalog catalog, string outputColumnName, string inputColumnName, int windowSize, int seriesLength, int trainSize, int horizon,
 bool isAdaptive = false, float discountFactor = 1, RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact, int? rank = null,
 int? maxRank = null, bool shouldStablize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string forcastingConfidentLowerBoundColumnName = null,
 string forcastingConfidentUpperBoundColumnName = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
 int? maxRank = null, bool shouldStabilize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string lowerBoundConfidenceColumn = null,
 string upperBoundConfidenceColumn = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
 new SsaForecastingEstimator(CatalogUtils.GetEnvironment(catalog), outputColumnName, inputColumnName, windowSize, seriesLength, trainSize,
 horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStablize, shouldMaintainInfo, maxGrowth, forcastingConfidentLowerBoundColumnName,
forcastingConfidentUpperBoundColumnName, confidenceLevel, variableHorizon);
 horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStabilize, shouldMaintainInfo, maxGrowth, lowerBoundConfidenceColumn,
upperBoundConfidenceColumn, confidenceLevel, variableHorizon);
 }
}

40 changes: 20 additions & 20 deletions
src/Microsoft.ML.TimeSeries/SSaForecasting.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -42,10 +42,10 @@ internal sealed class Options : TransformInputBase
 public string Name;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname", SortOrder = 3)]
 public string ForcastingConfidentLowerBoundColumnName;
 public string LowerBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname", SortOrder = 3)]
 public string ForcastingConfidentUpperBoundColumnName;
 public string UpperBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The discount factor in [0,1] used for online updates.", ShortName = "disc", SortOrder = 5)]
 public float DiscountFactor = 1;
Expand All@@ -67,7 +67,7 @@ internal sealed class Options : TransformInputBase
 public int? MaxRank = null;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the model should be stabilized.", SortOrder = 3)]
 public bool ShouldStablize = true;
 public bool ShouldStabilize = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the meta information for the model needs to be maintained.", SortOrder = 3)]
 public bool ShouldMaintainInfo = false;
Expand DownExpand Up@@ -97,14 +97,14 @@ public BaseArguments(Options options)
 {
 Source = options.Source;
 Name = options.Name;
ForcastingConfidentLowerBoundColumnName = options.ForcastingConfidentLowerBoundColumnName;
ForcastingConfidentUpperBoundColumnName = options.ForcastingConfidentUpperBoundColumnName;
LowerBoundConfidenceColumn = options.LowerBoundConfidenceColumn;
UpperBoundConfidenceColumn = options.UpperBoundConfidenceColumn;
 WindowSize = options.WindowSize;
 DiscountFactor = options.DiscountFactor;
 IsAdaptive = options.IsAdaptive;
 RankSelectionMethod = options.RankSelectionMethod;
 Rank = options.Rank;
 ShouldStablize = options.ShouldStablize;
 ShouldStablize = options.ShouldStabilize;
 MaxGrowth = options.MaxGrowth;
 SeriesLength = options.SeriesLength;
 TrainSize = options.TrainSize;
Expand DownExpand Up@@ -255,11 +255,11 @@ public sealed class SsaForecastingEstimator : IEstimator<SsaForecastingTransform
 /// <param name="rank">The desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
 /// If set to null, the rank is automatically determined based on prediction error minimization.</param>
 /// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
 /// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
 /// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
 /// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="confidenceLevel">The confidence level for forecasting.</param>
 /// <param name="variableHorizon">Set this to true if horizon will change after training.</param>
 internal SsaForecastingEstimator(IHostEnvironment env,
Expand All@@ -274,11 +274,11 @@ internal SsaForecastingEstimator(IHostEnvironment env,
 RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact,
 int? rank = null,
 int? maxRank = null,
 bool shouldStablize = true,
 bool shouldStabilize = true,
 bool shouldMaintainInfo = false,
 GrowthRatio? maxGrowth = null,
 string forcastingConfidentLowerBoundColumnName = null,
 string forcastingConfidentUpperBoundColumnName = null,
 string lowerBoundConfidenceColumn = null,
 string upperBoundConfidenceColumn = null,
 float confidenceLevel = 0.95f,
 bool variableHorizon = false)
 : this(env, new SsaForecastingTransformer.Options
Expand All@@ -291,12 +291,12 @@ internal SsaForecastingEstimator(IHostEnvironment env,
 RankSelectionMethod = rankSelectionMethod,
 Rank = rank,
 MaxRank = maxRank,
ShouldStablize = shouldStablize,
ShouldStabilize = shouldStabilize,
 ShouldMaintainInfo = shouldMaintainInfo,
 MaxGrowth = maxGrowth,
 ConfidenceLevel = confidenceLevel,
ForcastingConfidentLowerBoundColumnName = forcastingConfidentLowerBoundColumnName,
ForcastingConfidentUpperBoundColumnName = forcastingConfidentUpperBoundColumnName,
LowerBoundConfidenceColumn = lowerBoundConfidenceColumn,
UpperBoundConfidenceColumn = upperBoundConfidenceColumn,
 SeriesLength = seriesLength,
 TrainSize = trainSize,
 VariableHorizon = variableHorizon,
Expand DownExpand Up@@ -344,14 +344,14 @@ public SchemaShape GetOutputSchema(SchemaShape inputSchema)
 resultDic[_options.Name] = new SchemaShape.Column(
 _options.Name, SchemaShape.Column.VectorKind.Vector, NumberDataViewType.Single, false);

 if (!string.IsNullOrEmpty(_options.ForcastingConfidentUpperBoundColumnName))
 if (!string.IsNullOrEmpty(_options.UpperBoundConfidenceColumn))
 {
 resultDic[_options.ForcastingConfidentLowerBoundColumnName] = new SchemaShape.Column(
 _options.ForcastingConfidentLowerBoundColumnName, SchemaShape.Column.VectorKind.Vector,
 resultDic[_options.LowerBoundConfidenceColumn] = new SchemaShape.Column(
 _options.LowerBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
 NumberDataViewType.Single, false);

 resultDic[_options.ForcastingConfidentUpperBoundColumnName] = new SchemaShape.Column(
 _options.ForcastingConfidentUpperBoundColumnName, SchemaShape.Column.VectorKind.Vector,
 resultDic[_options.UpperBoundConfidenceColumn] = new SchemaShape.Column(
 _options.UpperBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
 NumberDataViewType.Single, false);
 }

Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.TimeSeries/SequentialForecastingTransformBase.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -28,11 +28,11 @@ internal abstract class ForecastingArgumentsBase

 [Argument(ArgumentType.Required, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname",
 SortOrder = 2)]
 public string ForcastingConfidentLowerBoundColumnName;
 public string LowerBoundConfidenceColumn;

 [Argument(ArgumentType.Required, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname",
 SortOrder = 2)]
 public string ForcastingConfidentUpperBoundColumnName;
 public string UpperBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The length of series from the begining used for training.", ShortName = "wnd",
 SortOrder = 3)]
Expand DownExpand Up@@ -67,8 +67,8 @@ private protected SequentialForecastingTransformBase(int windowSize, int initial
 }

 private protected SequentialForecastingTransformBase(ForecastingArgumentsBase args, string name, int outputLength, IHostEnvironment env)
 : this(args.TrainSize, args.SeriesLength, args.Source, args.ForcastingConfidentLowerBoundColumnName,
 args.ForcastingConfidentUpperBoundColumnName, args.Name, name, outputLength, env)
 : this(args.TrainSize, args.SeriesLength, args.Source, args.LowerBoundConfidenceColumn,
 args.UpperBoundConfidenceColumn, args.Name, name, outputLength, env)
 {
 }

Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.TimeSeries/SsaForecastingBase.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -127,16 +127,16 @@ internal sealed class SsaForecastingBase : SequentialForecastingTransformBase<fl
 internal SequenceModelerBase<Single, Single> Model;

 public SsaForecastingBase(SsaForecastingOptions options, string name, IHostEnvironment env, SsaForecastingBaseWrapper parent)
 : base(options.TrainSize, 0, options.Source, options.Name, options.ForcastingConfidentLowerBoundColumnName,
 options.ForcastingConfidentUpperBoundColumnName, name, options.VariableHorizon ? 0: options.Horizon, env)
 : base(options.TrainSize, 0, options.Source, options.Name, options.LowerBoundConfidenceColumn,
 options.UpperBoundConfidenceColumn, name, options.VariableHorizon ? 0: options.Horizon, env)
 {
 Host.CheckUserArg(0 <= options.DiscountFactor && options.DiscountFactor <= 1, nameof(options.DiscountFactor), "Must be in the range [0, 1].");
 IsAdaptive = options.IsAdaptive;
 Horizon = options.Horizon;
 ConfidenceLevel = options.ConfidenceLevel;
 // Creating the master SSA model
 Model = new AdaptiveSingularSpectrumSequenceModelerInternal(Host, options.TrainSize, options.SeriesLength, options.WindowSize,
 options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.ForcastingConfidentLowerBoundColumnName),
 options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.LowerBoundConfidenceColumn),
 options.ShouldStablize, options.ShouldMaintainInfo, options.MaxGrowth);

 StateRef = new State();
Expand Down

6 changes: 3 additions & 3 deletions
test/BaselineOutput/Common/EntryPoints/core_manifest.json

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Original file line numberDiff line numberDiff line change
Expand Up@@ -4095,7 +4095,7 @@
 "Default": false
 },
 {
 "Name": "ForcastingConfidentLowerBoundColumnName",
 "Name": "LowerBoundConfidenceColumn",
 "Type": "String",
 "Desc": "The name of the confidence interval lower bound column.",
 "Aliases": [
Expand All@@ -4107,7 +4107,7 @@
 "Default": null
 },
 {
 "Name": "ForcastingConfidentUpperBoundColumnName",
 "Name": "UpperBoundConfidenceColumn",
 "Type": "String",
 "Desc": "The name of the confidence interval upper bound column.",
 "Aliases": [
Expand DownExpand Up@@ -4153,7 +4153,7 @@
 "Default": null
 },
 {
 "Name": "ShouldStablize",
 "Name": "ShouldStabilize",
 "Type": "Bool",
 "Desc": "The flag determining whether the model should be stabilized.",
 "Required": false,
Expand Down

12 changes: 6 additions & 6 deletions
test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -338,8 +338,8 @@ public void SsaForecast()
 ConfidenceLevel = 0.95f,
 Source = "Value",
 Name = "Forecast",
ForcastingConfidentLowerBoundColumnName = "MinCnf",
ForcastingConfidentUpperBoundColumnName = "MaxCnf",
LowerBoundConfidenceColumn = "MinCnf",
UpperBoundConfidenceColumn = "MaxCnf",
 WindowSize = 10,
 SeriesLength = 11,
 TrainSize = 22,
Expand DownExpand Up@@ -397,8 +397,8 @@ public void SsaForecastPredictionEngine()
 SeriesLength = 11,
 TrainSize = 22,
 Horizon = 4,
ForcastingConfidentLowerBoundColumnName = "ConfidenceLowerBound",
ForcastingConfidentUpperBoundColumnName = "ConfidenceUpperBound",
LowerBoundConfidenceColumn = "ConfidenceLowerBound",
UpperBoundConfidenceColumn = "ConfidenceUpperBound",
 VariableHorizon = true
 };

Expand All@@ -413,8 +413,8 @@ public void SsaForecastPredictionEngine()
 var model = ml.Transforms.Text.FeaturizeText("Text_Featurized", "Text")
 .Append(ml.Transforms.Conversion.ConvertType("Value", "Value", DataKind.Single))
 .Append(ml.Forecasting.ForecastBySsa("Forecast", "Value", 10, 11, 22, 4,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound", variableHorizon: true))
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound", variableHorizon: true))
 .Append(ml.Transforms.Concatenate("Forecast", "Forecast", "ConfidenceLowerBound", "ConfidenceUpperBound"))
 .Fit(dataView);

Expand Down

4 changes: 2 additions & 2 deletions
test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -95,8 +95,8 @@ void TestSsaForecastingEstimator()

 // Train
 var pipe = new SsaForecastingEstimator(Env, "Forecast", "Value", 10, 11, 22, 4,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound");

 var xyData = new List<TestDataXY> { new TestDataXY() { A = new float[inputSize] } };
 var stringData = new List<TestDataDifferntType> { new TestDataDifferntType() { data_0 = new string[inputSize] } };
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Fix typo in time series forecasting API.#3944

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Fix typo in time series forecasting API.
#3944
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584ae66

Fix typo in time series forecasting API.


codemzs Jul 1, 2019
327409a

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codemzs Jul 1, 2019

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4 changes: 2 additions & 2 deletions
...s/Microsoft.ML.Samples/Dynamic/Transforms/TimeSeries/ForecastingWithConfidenceInterval.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -48,8 +48,8 @@ public static void Example()
 // Instantiate the forecasting model.
 var model = ml.Forecasting.ForecastBySsa(outputColumnName, inputColumnName, 5, 11, data.Count, 5,
 confidenceLevel: 0.95f,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound");

 // Train.
 var transformer = model.Fit(dataView);
Expand Down

14 changes: 7 additions & 7 deletions
src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -164,11 +164,11 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
 /// <param name="rank">The desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
 /// If set to null, the rank is automatically determined based on prediction error minimization.</param>
 /// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
 /// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
 /// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
 /// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="confidenceLevel">The confidence level for forecasting.</param>
 /// <param name="variableHorizon">Set this to true if horizon will change after training(at prediction time).</param>
 /// <example>
Expand All@@ -182,10 +182,10 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
 public static SsaForecastingEstimator ForecastBySsa(
 this ForecastingCatalog catalog, string outputColumnName, string inputColumnName, int windowSize, int seriesLength, int trainSize, int horizon,
 bool isAdaptive = false, float discountFactor = 1, RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact, int? rank = null,
 int? maxRank = null, bool shouldStablize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string forcastingConfidentLowerBoundColumnName = null,
 string forcastingConfidentUpperBoundColumnName = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
 int? maxRank = null, bool shouldStabilize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string lowerBoundConfidenceColumn = null,
 string upperBoundConfidenceColumn = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
 new SsaForecastingEstimator(CatalogUtils.GetEnvironment(catalog), outputColumnName, inputColumnName, windowSize, seriesLength, trainSize,
 horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStablize, shouldMaintainInfo, maxGrowth, forcastingConfidentLowerBoundColumnName,
forcastingConfidentUpperBoundColumnName, confidenceLevel, variableHorizon);
 horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStabilize, shouldMaintainInfo, maxGrowth, lowerBoundConfidenceColumn,
upperBoundConfidenceColumn, confidenceLevel, variableHorizon);
 }
}

40 changes: 20 additions & 20 deletions
src/Microsoft.ML.TimeSeries/SSaForecasting.cs

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -42,10 +42,10 @@ internal sealed class Options : TransformInputBase
 public string Name;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname", SortOrder = 3)]
 public string ForcastingConfidentLowerBoundColumnName;
 public string LowerBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname", SortOrder = 3)]
 public string ForcastingConfidentUpperBoundColumnName;
 public string UpperBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The discount factor in [0,1] used for online updates.", ShortName = "disc", SortOrder = 5)]
 public float DiscountFactor = 1;
Expand All@@ -67,7 +67,7 @@ internal sealed class Options : TransformInputBase
 public int? MaxRank = null;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the model should be stabilized.", SortOrder = 3)]
 public bool ShouldStablize = true;
 public bool ShouldStabilize = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the meta information for the model needs to be maintained.", SortOrder = 3)]
 public bool ShouldMaintainInfo = false;
Expand DownExpand Up@@ -97,14 +97,14 @@ public BaseArguments(Options options)
 {
 Source = options.Source;
 Name = options.Name;
ForcastingConfidentLowerBoundColumnName = options.ForcastingConfidentLowerBoundColumnName;
ForcastingConfidentUpperBoundColumnName = options.ForcastingConfidentUpperBoundColumnName;
LowerBoundConfidenceColumn = options.LowerBoundConfidenceColumn;
UpperBoundConfidenceColumn = options.UpperBoundConfidenceColumn;
 WindowSize = options.WindowSize;
 DiscountFactor = options.DiscountFactor;
 IsAdaptive = options.IsAdaptive;
 RankSelectionMethod = options.RankSelectionMethod;
 Rank = options.Rank;
 ShouldStablize = options.ShouldStablize;
 ShouldStablize = options.ShouldStabilize;
 MaxGrowth = options.MaxGrowth;
 SeriesLength = options.SeriesLength;
 TrainSize = options.TrainSize;
Expand DownExpand Up@@ -255,11 +255,11 @@ public sealed class SsaForecastingEstimator : IEstimator<SsaForecastingTransform
 /// <param name="rank">The desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
 /// If set to null, the rank is automatically determined based on prediction error minimization.</param>
 /// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
 /// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
 /// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
 /// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="confidenceLevel">The confidence level for forecasting.</param>
 /// <param name="variableHorizon">Set this to true if horizon will change after training.</param>
 internal SsaForecastingEstimator(IHostEnvironment env,
Expand All@@ -274,11 +274,11 @@ internal SsaForecastingEstimator(IHostEnvironment env,
 RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact,
 int? rank = null,
 int? maxRank = null,
 bool shouldStablize = true,
 bool shouldStabilize = true,
 bool shouldMaintainInfo = false,
 GrowthRatio? maxGrowth = null,
 string forcastingConfidentLowerBoundColumnName = null,
 string forcastingConfidentUpperBoundColumnName = null,
 string lowerBoundConfidenceColumn = null,
 string upperBoundConfidenceColumn = null,
 float confidenceLevel = 0.95f,
 bool variableHorizon = false)
 : this(env, new SsaForecastingTransformer.Options
Expand All@@ -291,12 +291,12 @@ internal SsaForecastingEstimator(IHostEnvironment env,
 RankSelectionMethod = rankSelectionMethod,
 Rank = rank,
 MaxRank = maxRank,
ShouldStablize = shouldStablize,
ShouldStabilize = shouldStabilize,
 ShouldMaintainInfo = shouldMaintainInfo,
 MaxGrowth = maxGrowth,
 ConfidenceLevel = confidenceLevel,
ForcastingConfidentLowerBoundColumnName = forcastingConfidentLowerBoundColumnName,
ForcastingConfidentUpperBoundColumnName = forcastingConfidentUpperBoundColumnName,
LowerBoundConfidenceColumn = lowerBoundConfidenceColumn,
UpperBoundConfidenceColumn = upperBoundConfidenceColumn,
 SeriesLength = seriesLength,
 TrainSize = trainSize,
 VariableHorizon = variableHorizon,
Expand DownExpand Up@@ -344,14 +344,14 @@ public SchemaShape GetOutputSchema(SchemaShape inputSchema)
 resultDic[_options.Name] = new SchemaShape.Column(
 _options.Name, SchemaShape.Column.VectorKind.Vector, NumberDataViewType.Single, false);

 if (!string.IsNullOrEmpty(_options.ForcastingConfidentUpperBoundColumnName))
 if (!string.IsNullOrEmpty(_options.UpperBoundConfidenceColumn))
 {
 resultDic[_options.ForcastingConfidentLowerBoundColumnName] = new SchemaShape.Column(
 _options.ForcastingConfidentLowerBoundColumnName, SchemaShape.Column.VectorKind.Vector,
 resultDic[_options.LowerBoundConfidenceColumn] = new SchemaShape.Column(
 _options.LowerBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
 NumberDataViewType.Single, false);

 resultDic[_options.ForcastingConfidentUpperBoundColumnName] = new SchemaShape.Column(
 _options.ForcastingConfidentUpperBoundColumnName, SchemaShape.Column.VectorKind.Vector,
 resultDic[_options.UpperBoundConfidenceColumn] = new SchemaShape.Column(
 _options.UpperBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
 NumberDataViewType.Single, false);
 }

Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.TimeSeries/SequentialForecastingTransformBase.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -28,11 +28,11 @@ internal abstract class ForecastingArgumentsBase

 [Argument(ArgumentType.Required, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname",
 SortOrder = 2)]
 public string ForcastingConfidentLowerBoundColumnName;
 public string LowerBoundConfidenceColumn;

 [Argument(ArgumentType.Required, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname",
 SortOrder = 2)]
 public string ForcastingConfidentUpperBoundColumnName;
 public string UpperBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The length of series from the begining used for training.", ShortName = "wnd",
 SortOrder = 3)]
Expand DownExpand Up@@ -67,8 +67,8 @@ private protected SequentialForecastingTransformBase(int windowSize, int initial
 }

 private protected SequentialForecastingTransformBase(ForecastingArgumentsBase args, string name, int outputLength, IHostEnvironment env)
 : this(args.TrainSize, args.SeriesLength, args.Source, args.ForcastingConfidentLowerBoundColumnName,
 args.ForcastingConfidentUpperBoundColumnName, args.Name, name, outputLength, env)
 : this(args.TrainSize, args.SeriesLength, args.Source, args.LowerBoundConfidenceColumn,
 args.UpperBoundConfidenceColumn, args.Name, name, outputLength, env)
 {
 }

Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.TimeSeries/SsaForecastingBase.cs

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -127,16 +127,16 @@ internal sealed class SsaForecastingBase : SequentialForecastingTransformBase<fl
 internal SequenceModelerBase<Single, Single> Model;

 public SsaForecastingBase(SsaForecastingOptions options, string name, IHostEnvironment env, SsaForecastingBaseWrapper parent)
 : base(options.TrainSize, 0, options.Source, options.Name, options.ForcastingConfidentLowerBoundColumnName,
 options.ForcastingConfidentUpperBoundColumnName, name, options.VariableHorizon ? 0: options.Horizon, env)
 : base(options.TrainSize, 0, options.Source, options.Name, options.LowerBoundConfidenceColumn,
 options.UpperBoundConfidenceColumn, name, options.VariableHorizon ? 0: options.Horizon, env)
 {
 Host.CheckUserArg(0 <= options.DiscountFactor && options.DiscountFactor <= 1, nameof(options.DiscountFactor), "Must be in the range [0, 1].");
 IsAdaptive = options.IsAdaptive;
 Horizon = options.Horizon;
 ConfidenceLevel = options.ConfidenceLevel;
 // Creating the master SSA model
 Model = new AdaptiveSingularSpectrumSequenceModelerInternal(Host, options.TrainSize, options.SeriesLength, options.WindowSize,
 options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.ForcastingConfidentLowerBoundColumnName),
 options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.LowerBoundConfidenceColumn),
 options.ShouldStablize, options.ShouldMaintainInfo, options.MaxGrowth);

 StateRef = new State();
Expand Down

6 changes: 3 additions & 3 deletions
test/BaselineOutput/Common/EntryPoints/core_manifest.json

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -4095,7 +4095,7 @@
 "Default": false
 },
 {
 "Name": "ForcastingConfidentLowerBoundColumnName",
 "Name": "LowerBoundConfidenceColumn",
 "Type": "String",
 "Desc": "The name of the confidence interval lower bound column.",
 "Aliases": [
Expand All@@ -4107,7 +4107,7 @@
 "Default": null
 },
 {
 "Name": "ForcastingConfidentUpperBoundColumnName",
 "Name": "UpperBoundConfidenceColumn",
 "Type": "String",
 "Desc": "The name of the confidence interval upper bound column.",
 "Aliases": [
Expand DownExpand Up@@ -4153,7 +4153,7 @@
 "Default": null
 },
 {
 "Name": "ShouldStablize",
 "Name": "ShouldStabilize",
 "Type": "Bool",
 "Desc": "The flag determining whether the model should be stabilized.",
 "Required": false,
Expand Down

12 changes: 6 additions & 6 deletions
test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -338,8 +338,8 @@ public void SsaForecast()
 ConfidenceLevel = 0.95f,
 Source = "Value",
 Name = "Forecast",
ForcastingConfidentLowerBoundColumnName = "MinCnf",
ForcastingConfidentUpperBoundColumnName = "MaxCnf",
LowerBoundConfidenceColumn = "MinCnf",
UpperBoundConfidenceColumn = "MaxCnf",
 WindowSize = 10,
 SeriesLength = 11,
 TrainSize = 22,
Expand DownExpand Up@@ -397,8 +397,8 @@ public void SsaForecastPredictionEngine()
 SeriesLength = 11,
 TrainSize = 22,
 Horizon = 4,
ForcastingConfidentLowerBoundColumnName = "ConfidenceLowerBound",
ForcastingConfidentUpperBoundColumnName = "ConfidenceUpperBound",
LowerBoundConfidenceColumn = "ConfidenceLowerBound",
UpperBoundConfidenceColumn = "ConfidenceUpperBound",
 VariableHorizon = true
 };

Expand All@@ -413,8 +413,8 @@ public void SsaForecastPredictionEngine()
 var model = ml.Transforms.Text.FeaturizeText("Text_Featurized", "Text")
 .Append(ml.Transforms.Conversion.ConvertType("Value", "Value", DataKind.Single))
 .Append(ml.Forecasting.ForecastBySsa("Forecast", "Value", 10, 11, 22, 4,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound", variableHorizon: true))
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound", variableHorizon: true))
 .Append(ml.Transforms.Concatenate("Forecast", "Forecast", "ConfidenceLowerBound", "ConfidenceUpperBound"))
 .Fit(dataView);

Expand Down

4 changes: 2 additions & 2 deletions
test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -95,8 +95,8 @@ void TestSsaForecastingEstimator()

 // Train
 var pipe = new SsaForecastingEstimator(Env, "Forecast", "Value", 10, 11, 22, 4,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound");

 var xyData = new List<TestDataXY> { new TestDataXY() { A = new float[inputSize] } };
 var stringData = new List<TestDataDifferntType> { new TestDataDifferntType() { data_0 = new string[inputSize] } };
Expand Down

, '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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Fix typo in time series forecasting API.#3944

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 Merged

codemzs
merged 2 commits into

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Jul 1, 2019
 Merged


Fix typo in time series forecasting API.
#3944
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584ae66

Fix typo in time series forecasting API.


codemzs Jul 1, 2019
327409a

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codemzs Jul 1, 2019

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4 changes: 2 additions & 2 deletions
...s/Microsoft.ML.Samples/Dynamic/Transforms/TimeSeries/ForecastingWithConfidenceInterval.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -48,8 +48,8 @@ public static void Example()
 // Instantiate the forecasting model.
 var model = ml.Forecasting.ForecastBySsa(outputColumnName, inputColumnName, 5, 11, data.Count, 5,
 confidenceLevel: 0.95f,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound");

 // Train.
 var transformer = model.Fit(dataView);
Expand Down

14 changes: 7 additions & 7 deletions
src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -164,11 +164,11 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
 /// <param name="rank">The desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
 /// If set to null, the rank is automatically determined based on prediction error minimization.</param>
 /// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
 /// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
 /// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
 /// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="confidenceLevel">The confidence level for forecasting.</param>
 /// <param name="variableHorizon">Set this to true if horizon will change after training(at prediction time).</param>
 /// <example>
Expand All@@ -182,10 +182,10 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
 public static SsaForecastingEstimator ForecastBySsa(
 this ForecastingCatalog catalog, string outputColumnName, string inputColumnName, int windowSize, int seriesLength, int trainSize, int horizon,
 bool isAdaptive = false, float discountFactor = 1, RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact, int? rank = null,
 int? maxRank = null, bool shouldStablize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string forcastingConfidentLowerBoundColumnName = null,
 string forcastingConfidentUpperBoundColumnName = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
 int? maxRank = null, bool shouldStabilize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string lowerBoundConfidenceColumn = null,
 string upperBoundConfidenceColumn = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
 new SsaForecastingEstimator(CatalogUtils.GetEnvironment(catalog), outputColumnName, inputColumnName, windowSize, seriesLength, trainSize,
 horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStablize, shouldMaintainInfo, maxGrowth, forcastingConfidentLowerBoundColumnName,
forcastingConfidentUpperBoundColumnName, confidenceLevel, variableHorizon);
 horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStabilize, shouldMaintainInfo, maxGrowth, lowerBoundConfidenceColumn,
upperBoundConfidenceColumn, confidenceLevel, variableHorizon);
 }
}

40 changes: 20 additions & 20 deletions
src/Microsoft.ML.TimeSeries/SSaForecasting.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -42,10 +42,10 @@ internal sealed class Options : TransformInputBase
 public string Name;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname", SortOrder = 3)]
 public string ForcastingConfidentLowerBoundColumnName;
 public string LowerBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname", SortOrder = 3)]
 public string ForcastingConfidentUpperBoundColumnName;
 public string UpperBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The discount factor in [0,1] used for online updates.", ShortName = "disc", SortOrder = 5)]
 public float DiscountFactor = 1;
Expand All@@ -67,7 +67,7 @@ internal sealed class Options : TransformInputBase
 public int? MaxRank = null;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the model should be stabilized.", SortOrder = 3)]
 public bool ShouldStablize = true;
 public bool ShouldStabilize = true;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the meta information for the model needs to be maintained.", SortOrder = 3)]
 public bool ShouldMaintainInfo = false;
Expand DownExpand Up@@ -97,14 +97,14 @@ public BaseArguments(Options options)
 {
 Source = options.Source;
 Name = options.Name;
ForcastingConfidentLowerBoundColumnName = options.ForcastingConfidentLowerBoundColumnName;
ForcastingConfidentUpperBoundColumnName = options.ForcastingConfidentUpperBoundColumnName;
LowerBoundConfidenceColumn = options.LowerBoundConfidenceColumn;
UpperBoundConfidenceColumn = options.UpperBoundConfidenceColumn;
 WindowSize = options.WindowSize;
 DiscountFactor = options.DiscountFactor;
 IsAdaptive = options.IsAdaptive;
 RankSelectionMethod = options.RankSelectionMethod;
 Rank = options.Rank;
 ShouldStablize = options.ShouldStablize;
 ShouldStablize = options.ShouldStabilize;
 MaxGrowth = options.MaxGrowth;
 SeriesLength = options.SeriesLength;
 TrainSize = options.TrainSize;
Expand DownExpand Up@@ -255,11 +255,11 @@ public sealed class SsaForecastingEstimator : IEstimator<SsaForecastingTransform
 /// <param name="rank">The desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
 /// If set to null, the rank is automatically determined based on prediction error minimization.</param>
 /// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
 /// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
 /// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
 /// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
 /// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
 /// <param name="confidenceLevel">The confidence level for forecasting.</param>
 /// <param name="variableHorizon">Set this to true if horizon will change after training.</param>
 internal SsaForecastingEstimator(IHostEnvironment env,
Expand All@@ -274,11 +274,11 @@ internal SsaForecastingEstimator(IHostEnvironment env,
 RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact,
 int? rank = null,
 int? maxRank = null,
 bool shouldStablize = true,
 bool shouldStabilize = true,
 bool shouldMaintainInfo = false,
 GrowthRatio? maxGrowth = null,
 string forcastingConfidentLowerBoundColumnName = null,
 string forcastingConfidentUpperBoundColumnName = null,
 string lowerBoundConfidenceColumn = null,
 string upperBoundConfidenceColumn = null,
 float confidenceLevel = 0.95f,
 bool variableHorizon = false)
 : this(env, new SsaForecastingTransformer.Options
Expand All@@ -291,12 +291,12 @@ internal SsaForecastingEstimator(IHostEnvironment env,
 RankSelectionMethod = rankSelectionMethod,
 Rank = rank,
 MaxRank = maxRank,
ShouldStablize = shouldStablize,
ShouldStabilize = shouldStabilize,
 ShouldMaintainInfo = shouldMaintainInfo,
 MaxGrowth = maxGrowth,
 ConfidenceLevel = confidenceLevel,
ForcastingConfidentLowerBoundColumnName = forcastingConfidentLowerBoundColumnName,
ForcastingConfidentUpperBoundColumnName = forcastingConfidentUpperBoundColumnName,
LowerBoundConfidenceColumn = lowerBoundConfidenceColumn,
UpperBoundConfidenceColumn = upperBoundConfidenceColumn,
 SeriesLength = seriesLength,
 TrainSize = trainSize,
 VariableHorizon = variableHorizon,
Expand DownExpand Up@@ -344,14 +344,14 @@ public SchemaShape GetOutputSchema(SchemaShape inputSchema)
 resultDic[_options.Name] = new SchemaShape.Column(
 _options.Name, SchemaShape.Column.VectorKind.Vector, NumberDataViewType.Single, false);

 if (!string.IsNullOrEmpty(_options.ForcastingConfidentUpperBoundColumnName))
 if (!string.IsNullOrEmpty(_options.UpperBoundConfidenceColumn))
 {
 resultDic[_options.ForcastingConfidentLowerBoundColumnName] = new SchemaShape.Column(
 _options.ForcastingConfidentLowerBoundColumnName, SchemaShape.Column.VectorKind.Vector,
 resultDic[_options.LowerBoundConfidenceColumn] = new SchemaShape.Column(
 _options.LowerBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
 NumberDataViewType.Single, false);

 resultDic[_options.ForcastingConfidentUpperBoundColumnName] = new SchemaShape.Column(
 _options.ForcastingConfidentUpperBoundColumnName, SchemaShape.Column.VectorKind.Vector,
 resultDic[_options.UpperBoundConfidenceColumn] = new SchemaShape.Column(
 _options.UpperBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
 NumberDataViewType.Single, false);
 }

Expand Down

8 changes: 4 additions & 4 deletions
src/Microsoft.ML.TimeSeries/SequentialForecastingTransformBase.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -28,11 +28,11 @@ internal abstract class ForecastingArgumentsBase

 [Argument(ArgumentType.Required, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname",
 SortOrder = 2)]
 public string ForcastingConfidentLowerBoundColumnName;
 public string LowerBoundConfidenceColumn;

 [Argument(ArgumentType.Required, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname",
 SortOrder = 2)]
 public string ForcastingConfidentUpperBoundColumnName;
 public string UpperBoundConfidenceColumn;

 [Argument(ArgumentType.AtMostOnce, HelpText = "The length of series from the begining used for training.", ShortName = "wnd",
 SortOrder = 3)]
Expand DownExpand Up@@ -67,8 +67,8 @@ private protected SequentialForecastingTransformBase(int windowSize, int initial
 }

 private protected SequentialForecastingTransformBase(ForecastingArgumentsBase args, string name, int outputLength, IHostEnvironment env)
 : this(args.TrainSize, args.SeriesLength, args.Source, args.ForcastingConfidentLowerBoundColumnName,
 args.ForcastingConfidentUpperBoundColumnName, args.Name, name, outputLength, env)
 : this(args.TrainSize, args.SeriesLength, args.Source, args.LowerBoundConfidenceColumn,
 args.UpperBoundConfidenceColumn, args.Name, name, outputLength, env)
 {
 }

Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.TimeSeries/SsaForecastingBase.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -127,16 +127,16 @@ internal sealed class SsaForecastingBase : SequentialForecastingTransformBase<fl
 internal SequenceModelerBase<Single, Single> Model;

 public SsaForecastingBase(SsaForecastingOptions options, string name, IHostEnvironment env, SsaForecastingBaseWrapper parent)
 : base(options.TrainSize, 0, options.Source, options.Name, options.ForcastingConfidentLowerBoundColumnName,
 options.ForcastingConfidentUpperBoundColumnName, name, options.VariableHorizon ? 0: options.Horizon, env)
 : base(options.TrainSize, 0, options.Source, options.Name, options.LowerBoundConfidenceColumn,
 options.UpperBoundConfidenceColumn, name, options.VariableHorizon ? 0: options.Horizon, env)
 {
 Host.CheckUserArg(0 <= options.DiscountFactor && options.DiscountFactor <= 1, nameof(options.DiscountFactor), "Must be in the range [0, 1].");
 IsAdaptive = options.IsAdaptive;
 Horizon = options.Horizon;
 ConfidenceLevel = options.ConfidenceLevel;
 // Creating the master SSA model
 Model = new AdaptiveSingularSpectrumSequenceModelerInternal(Host, options.TrainSize, options.SeriesLength, options.WindowSize,
 options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.ForcastingConfidentLowerBoundColumnName),
 options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.LowerBoundConfidenceColumn),
 options.ShouldStablize, options.ShouldMaintainInfo, options.MaxGrowth);

 StateRef = new State();
Expand Down

6 changes: 3 additions & 3 deletions
test/BaselineOutput/Common/EntryPoints/core_manifest.json

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Original file line numberDiff line numberDiff line change
Expand Up@@ -4095,7 +4095,7 @@
 "Default": false
 },
 {
 "Name": "ForcastingConfidentLowerBoundColumnName",
 "Name": "LowerBoundConfidenceColumn",
 "Type": "String",
 "Desc": "The name of the confidence interval lower bound column.",
 "Aliases": [
Expand All@@ -4107,7 +4107,7 @@
 "Default": null
 },
 {
 "Name": "ForcastingConfidentUpperBoundColumnName",
 "Name": "UpperBoundConfidenceColumn",
 "Type": "String",
 "Desc": "The name of the confidence interval upper bound column.",
 "Aliases": [
Expand DownExpand Up@@ -4153,7 +4153,7 @@
 "Default": null
 },
 {
 "Name": "ShouldStablize",
 "Name": "ShouldStabilize",
 "Type": "Bool",
 "Desc": "The flag determining whether the model should be stabilized.",
 "Required": false,
Expand Down

12 changes: 6 additions & 6 deletions
test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -338,8 +338,8 @@ public void SsaForecast()
 ConfidenceLevel = 0.95f,
 Source = "Value",
 Name = "Forecast",
ForcastingConfidentLowerBoundColumnName = "MinCnf",
ForcastingConfidentUpperBoundColumnName = "MaxCnf",
LowerBoundConfidenceColumn = "MinCnf",
UpperBoundConfidenceColumn = "MaxCnf",
 WindowSize = 10,
 SeriesLength = 11,
 TrainSize = 22,
Expand DownExpand Up@@ -397,8 +397,8 @@ public void SsaForecastPredictionEngine()
 SeriesLength = 11,
 TrainSize = 22,
 Horizon = 4,
ForcastingConfidentLowerBoundColumnName = "ConfidenceLowerBound",
ForcastingConfidentUpperBoundColumnName = "ConfidenceUpperBound",
LowerBoundConfidenceColumn = "ConfidenceLowerBound",
UpperBoundConfidenceColumn = "ConfidenceUpperBound",
 VariableHorizon = true
 };

Expand All@@ -413,8 +413,8 @@ public void SsaForecastPredictionEngine()
 var model = ml.Transforms.Text.FeaturizeText("Text_Featurized", "Text")
 .Append(ml.Transforms.Conversion.ConvertType("Value", "Value", DataKind.Single))
 .Append(ml.Forecasting.ForecastBySsa("Forecast", "Value", 10, 11, 22, 4,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound", variableHorizon: true))
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound", variableHorizon: true))
 .Append(ml.Transforms.Concatenate("Forecast", "Forecast", "ConfidenceLowerBound", "ConfidenceUpperBound"))
 .Fit(dataView);

Expand Down

4 changes: 2 additions & 2 deletions
test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -95,8 +95,8 @@ void TestSsaForecastingEstimator()

 // Train
 var pipe = new SsaForecastingEstimator(Env, "Forecast", "Value", 10, 11, 22, 4,
forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
lowerBoundConfidenceColumn: "ConfidenceLowerBound",
upperBoundConfidenceColumn: "ConfidenceUpperBound");

 var xyData = new List<TestDataXY> { new TestDataXY() { A = new float[inputSize] } };
 var stringData = new List<TestDataDifferntType> { new TestDataDifferntType() { data_0 = new string[inputSize] } };
Expand Down