Added convenience constructor for set of transforms (#380).

src/Microsoft.ML.Data/Transforms/ConcatTransform.cs

@@ -90,6 +90,19 @@ public bool TryUnparse(StringBuilder sb)
 
  public sealed class Arguments : TransformInputBase
  {
+ public Arguments()
+ {
+ }
+
+ public Arguments(string name, params string[] source)
+ {
+ Column = new[] { new Column()
+ {
+ Name = name,
+ Source = source
+ }};
+ }
+
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:srcs)", ShortName = "col", SortOrder = 1)]
  public Column[] Column;
  }
@@ -527,6 +540,18 @@ private static VersionInfo GetVersionInfo()
 
  public override ISchema Schema => _bindings;
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Input columns to concatenate.</param>
+ public ConcatTransform(IHostEnvironment env, IDataView input, string name, params string[] source)
+ : this(env, new Arguments(name, source), input)
+ {
+ }
+
  /// <summary>
  /// Public constructor corresponding to SignatureDataTransform.
  /// </summary>

src/Microsoft.ML.Data/Transforms/CopyColumnsTransform.cs

@@ -64,6 +64,18 @@ private static VersionInfo GetVersionInfo()
 
  private const string RegistrationName = "CopyColumns";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be copied.</param>
+ public CopyColumnsTransform(IHostEnvironment env, IDataView input, string name, string source)
+ : this(env, new Arguments(){ Column = new[] { new Column() { Source = source, Name = name }}}, input)
+ {
+ }
+
  public CopyColumnsTransform(IHostEnvironment env, Arguments args, IDataView input)
  : base(env, RegistrationName, env.CheckRef(args, nameof(args)).Column, input, null)
  {

src/Microsoft.ML.Data/Transforms/DropColumnsTransform.cs

@@ -237,6 +237,17 @@ private static VersionInfo GetVersionInfo()
  private const string DropRegistrationName = "DropColumns";
  private const string KeepRegistrationName = "KeepColumns";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="columnsToDrop">Name of the columns to be dropped.</param>
+ public DropColumnsTransform(IHostEnvironment env, IDataView input, params string[] columnsToDrop)
+ :this(env, new Arguments() { Column = columnsToDrop }, input)
+ {
+ }
+
  /// <summary>
  /// Public constructor corresponding to SignatureDataTransform.
  /// </summary>
@@ -383,4 +394,17 @@ public ValueGetter<TValue> GetGetter<TValue>(int col)
  }
  }
  }
+
+ public class KeepColumnsTransform
+ {
+ /// <summary>
+ /// A helper method to create <see cref="KeepColumnsTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="columnsToKeep">Name of the columns to be kept. All other columns will be removed.</param>
+ /// <returns></returns>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, params string[] columnsToKeep)
+ => new DropColumnsTransform(env, new DropColumnsTransform.KeepArguments() { Column = columnsToKeep }, input);
+ }
 }

src/Microsoft.ML.Data/Transforms/NAFilter.cs

@@ -28,13 +28,18 @@ namespace Microsoft.ML.Runtime.Data
 {
  public sealed class NAFilter : FilterBase
  {
+ private static class Defaults
+ {
+ public const bool Complement = false;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Column", ShortName = "col", SortOrder = 1)]
  public string[] Column;
 
  [Argument(ArgumentType.Multiple, HelpText = "If true, keep only rows that contain NA values, and filter the rest.")]
- public bool Complement;
+ public bool Complement = Defaults.Complement;
  }
 
  private sealed class ColInfo
@@ -72,6 +77,18 @@ private static VersionInfo GetVersionInfo()
  private readonly bool _complement;
  private const string RegistrationName = "MissingValueFilter";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="complement">If true, keep only rows that contain NA values, and filter the rest.</param>
+ /// <param name="columns">Name of the columns. Only these columns will be used to filter rows having 'NA' values.</param>
+ public NAFilter(IHostEnvironment env, IDataView input, bool complement = Defaults.Complement, params string[] columns)
+ : this(env, new Arguments() { Column = columns, Complement = complement }, input)
+ {
+ }
+
  public NAFilter(IHostEnvironment env, Arguments args, IDataView input)
  : base(env, RegistrationName, input)
  {

src/Microsoft.ML.Transforms/BootstrapSampleTransform.cs

@@ -25,20 +25,27 @@ namespace Microsoft.ML.Runtime.Data
  /// </summary>
  public sealed class BootstrapSampleTransform : FilterBase
  {
+ private static class Defaults
+ {
+ public const bool Complement = false;
+ public const bool ShuffleInput = true;
+ public const int PoolSize = 1000;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether this is the out-of-bag sample, that is, all those rows that are not selected by the transform.",
  ShortName = "comp")]
- public bool Complement;
+ public bool Complement = Defaults.Complement;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "The random seed. If unspecified random state will be instead derived from the environment.")]
  public uint? Seed;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.", ShortName = "si")]
- public bool ShuffleInput = true;
+ public bool ShuffleInput = Defaults.ShuffleInput;
 
  [Argument(ArgumentType.LastOccurenceWins, HelpText = "When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.", ShortName = "pool")]
- public int PoolSize = 1000;
+ public int PoolSize = Defaults.PoolSize;
  }
 
  internal const string Summary = "Approximate bootstrap sampling.";
@@ -76,6 +83,25 @@ public BootstrapSampleTransform(IHostEnvironment env, Arguments args, IDataView
  _poolSize = args.PoolSize;
  }
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="complement">Whether this is the out-of-bag sample, that is, all those rows that are not selected by the transform.</param>
+ /// <param name="seed">The random seed. If unspecified random state will be instead derived from the environment.</param>
+ /// <param name="shuffleInput">Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.</param>
+ /// <param name="poolSize">When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.</param>
+ public BootstrapSampleTransform(IHostEnvironment env, 
+ IDataView input, 
+ bool complement = Defaults.Complement, 
+ uint? seed = null, 
+ bool shuffleInput = Defaults.ShuffleInput, 
+ int poolSize = Defaults.PoolSize)
+ : this(env, new Arguments() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
+ {
+ }
+
  private BootstrapSampleTransform(IHost host, ModelLoadContext ctx, IDataView input)
  : base(host, input)
  {

src/Microsoft.ML.Transforms/CategoricalHashTransform.cs

@@ -86,6 +86,15 @@ public bool TryUnparse(StringBuilder sb)
  }
  }
 
+ private static class Defaults
+ {
+ public const int HashBits = 16;
+ public const uint Seed = 314489979;
+ public const bool Ordered = true;
+ public const int InvertHash = 0;
+ public const CategoricalTransform.OutputKind OutputKind = CategoricalTransform.OutputKind.Bag;
+ }
+
  /// <summary>
  /// This class is a merger of <see cref="HashTransform.Arguments"/> and <see cref="KeyToVectorTransform.Arguments"/>
  /// with join option removed
@@ -97,29 +106,61 @@ public sealed class Arguments : TransformInputBase
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Number of bits to hash into. Must be between 1 and 30, inclusive.",
  ShortName = "bits", SortOrder = 2)]
- public int HashBits = 16;
+ public int HashBits = Defaults.HashBits;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Hashing seed")]
- public uint Seed = 314489979;
+ public uint Seed = Defaults.Seed;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether the position of each term should be included in the hash", ShortName = "ord")]
- public bool Ordered = true;
+ public bool Ordered = Defaults.Ordered;
 
  [Argument(ArgumentType.AtMostOnce,
  HelpText = "Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit.",
  ShortName = "ih")]
- public int InvertHash;
+ public int InvertHash = Defaults.InvertHash;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Output kind: Bag (multi-set vector), Ind (indicator vector), or Key (index)",
  ShortName = "kind", SortOrder = 102)]
- public CategoricalTransform.OutputKind OutputKind = CategoricalTransform.OutputKind.Bag;
+ public CategoricalTransform.OutputKind OutputKind = Defaults.OutputKind;
  }
 
  internal const string Summary = "Converts the categorical value into an indicator array by hashing the value and using the hash as an index in the "
  + "bag. If the input column is a vector, a single indicator bag is returned for it.";
 
  public const string UserName = "Categorical Hash Transform";
 
+ /// <summary>
+ /// A helper method to create <see cref="CategoricalHashTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
+ /// <param name="hashBits">Number of bits to hash into. Must be between 1 and 30, inclusive.</param>
+ /// <param name="invertHash">Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit.</param>
+ /// <param name="outputKind">The type of output expected.</param>
+ public static IDataTransform Create(IHostEnvironment env, 
+ IDataView input, 
+ string name, 
+ string source =null, 
+ int hashBits = Defaults.HashBits, 
+ int invertHash = Defaults.InvertHash, 
+ CategoricalTransform.OutputKind outputKind = Defaults.OutputKind)
+ {
+ var args = new Arguments()
+ {
+ Column = new[] { new Column(){
+ Source = source ?? name,
+ Name = name
+ }
+ },
+ HashBits = hashBits,
+ InvertHash = invertHash,
+ OutputKind = outputKind
+ };
+ return Create(env, args, input);
+ }
+
  public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataView input)
  {
  Contracts.CheckValue(env, nameof(env));

src/Microsoft.ML.Transforms/CategoricalTransform.cs

@@ -38,15 +38,27 @@ public static class CategoricalTransform
  {
  public enum OutputKind : byte
  {
+ /// <summary>
+ /// Output is a bag (multi-set) vector
+ /// </summary>
  [TGUI(Label = "Output is a bag (multi-set) vector")]
  Bag = 1,
 
+ /// <summary>
+ /// Output is an indicator vector
+ /// </summary>
  [TGUI(Label = "Output is an indicator vector")]
  Ind = 2,
 
+ /// <summary>
+ /// Output is a key value
+ /// </summary>
  [TGUI(Label = "Output is a key value")]
  Key = 3,
 
+ /// <summary>
+ /// Output is binary encoded
+ /// </summary>
  [TGUI(Label = "Output is binary encoded")]
  Bin = 4,
  }
@@ -96,14 +108,19 @@ public bool TryUnparse(StringBuilder sb)
  }
  }
 
+ private static class Defaults
+ {
+ public const OutputKind OutKind = OutputKind.Ind;
+ }
+
  public sealed class Arguments : TermTransform.ArgumentsBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", ShortName = "col", SortOrder = 1)]
  public Column[] Column;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Output kind: Bag (multi-set vector), Ind (indicator vector), or Key (index)",
  ShortName = "kind", SortOrder = 102)]
- public OutputKind OutputKind = OutputKind.Ind;
+ public OutputKind OutputKind = Defaults.OutKind;
 
  public Arguments()
  {
@@ -118,6 +135,28 @@ public Arguments()
 
  public const string UserName = "Categorical Transform";
 
+ /// <summary>
+ /// A helper method to create <see cref="CategoricalTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
+ /// <param name="outputKind">The type of output expected.</param>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, string name, string source = null, OutputKind outputKind = Defaults.OutKind)
+ {
+ var args = new Arguments()
+ {
+ Column = new[] { new Column(){
+ Source = source ?? name,
+ Name = name
+ }
+ },
+ OutputKind = outputKind
+ };
+ return Create(env, args, input);
+ }
+
  public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataView input)
  {
  Contracts.CheckValue(env, nameof(env));

src/Microsoft.ML.Transforms/CountFeatureSelection.cs

@@ -28,17 +28,40 @@ public static class CountFeatureSelectionTransform
  public const string Summary = "Selects the slots for which the count of non-default values is greater than or equal to a threshold.";
  public const string UserName = "Count Feature Selection Transform";
 
+ private static class Defaults
+ {
+ public const long Count = 1;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Columns to use for feature selection", ShortName = "col", SortOrder = 1)]
  public string[] Column;
 
  [Argument(ArgumentType.Required, HelpText = "If the count of non-default values for a slot is greater than or equal to this threshold, the slot is preserved", ShortName = "c", SortOrder = 1)]
- public long Count = 1;
+ public long Count = Defaults.Count;
  }
 
  internal static string RegistrationName = "CountFeatureSelectionTransform";
 
+ /// <summary>
+ /// A helper method to create CountFeatureSelection transform for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="count">If the count of non-default values for a slot is greater than or equal to this threshold, the slot is preserved.</param>
+ /// <param name="columns">Columns to use for feature selection.</param>
+ /// <returns></returns>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, long count = Defaults.Count, params string[] columns)
+ {
+ var args = new Arguments()
+ {
+ Column = columns,
+ Count = count
+ };
+ return Create(env, args, input);
+ }
+
  /// <summary>
  /// Create method corresponding to SignatureDataTransform.
  /// </summary>

src/Microsoft.ML.Data/Transforms/ConcatTransform.cs

@@ -90,6 +90,19 @@ public bool TryUnparse(StringBuilder sb)
 
  public sealed class Arguments : TransformInputBase
  {
+ public Arguments()
+ {
+ }
+
+ public Arguments(string name, params string[] source)
+ {
+ Column = new[] { new Column()
+ {
+ Name = name,
+ Source = source
+ }};
+ }
+
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:srcs)", ShortName = "col", SortOrder = 1)]
  public Column[] Column;
  }
@@ -527,6 +540,18 @@ private static VersionInfo GetVersionInfo()
 
  public override ISchema Schema => _bindings;
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Input columns to concatenate.</param>
+ public ConcatTransform(IHostEnvironment env, IDataView input, string name, params string[] source)
+ : this(env, new Arguments(name, source), input)
+ {
+ }
+
  /// <summary>
  /// Public constructor corresponding to SignatureDataTransform.
  /// </summary>

src/Microsoft.ML.Data/Transforms/CopyColumnsTransform.cs

@@ -64,6 +64,18 @@ private static VersionInfo GetVersionInfo()
 
  private const string RegistrationName = "CopyColumns";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be copied.</param>
+ public CopyColumnsTransform(IHostEnvironment env, IDataView input, string name, string source)
+ : this(env, new Arguments(){ Column = new[] { new Column() { Source = source, Name = name }}}, input)
+ {
+ }
+
  public CopyColumnsTransform(IHostEnvironment env, Arguments args, IDataView input)
  : base(env, RegistrationName, env.CheckRef(args, nameof(args)).Column, input, null)
  {

src/Microsoft.ML.Data/Transforms/DropColumnsTransform.cs

@@ -237,6 +237,17 @@ private static VersionInfo GetVersionInfo()
  private const string DropRegistrationName = "DropColumns";
  private const string KeepRegistrationName = "KeepColumns";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="columnsToDrop">Name of the columns to be dropped.</param>
+ public DropColumnsTransform(IHostEnvironment env, IDataView input, params string[] columnsToDrop)
+ :this(env, new Arguments() { Column = columnsToDrop }, input)
+ {
+ }
+
  /// <summary>
  /// Public constructor corresponding to SignatureDataTransform.
  /// </summary>
@@ -383,4 +394,17 @@ public ValueGetter<TValue> GetGetter<TValue>(int col)
  }
  }
  }
+
+ public class KeepColumnsTransform
+ {
+ /// <summary>
+ /// A helper method to create <see cref="KeepColumnsTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="columnsToKeep">Name of the columns to be kept. All other columns will be removed.</param>
+ /// <returns></returns>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, params string[] columnsToKeep)
+ => new DropColumnsTransform(env, new DropColumnsTransform.KeepArguments() { Column = columnsToKeep }, input);
+ }
 }

src/Microsoft.ML.Data/Transforms/NAFilter.cs

@@ -28,13 +28,18 @@ namespace Microsoft.ML.Runtime.Data
 {
  public sealed class NAFilter : FilterBase
  {
+ private static class Defaults
+ {
+ public const bool Complement = false;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Column", ShortName = "col", SortOrder = 1)]
  public string[] Column;
 
  [Argument(ArgumentType.Multiple, HelpText = "If true, keep only rows that contain NA values, and filter the rest.")]
- public bool Complement;
+ public bool Complement = Defaults.Complement;
  }
 
  private sealed class ColInfo
@@ -72,6 +77,18 @@ private static VersionInfo GetVersionInfo()
  private readonly bool _complement;
  private const string RegistrationName = "MissingValueFilter";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="complement">If true, keep only rows that contain NA values, and filter the rest.</param>
+ /// <param name="columns">Name of the columns. Only these columns will be used to filter rows having 'NA' values.</param>
+ public NAFilter(IHostEnvironment env, IDataView input, bool complement = Defaults.Complement, params string[] columns)
+ : this(env, new Arguments() { Column = columns, Complement = complement }, input)
+ {
+ }
+
  public NAFilter(IHostEnvironment env, Arguments args, IDataView input)
  : base(env, RegistrationName, input)
  {

src/Microsoft.ML.Transforms/BootstrapSampleTransform.cs

@@ -25,20 +25,27 @@ namespace Microsoft.ML.Runtime.Data
  /// </summary>
  public sealed class BootstrapSampleTransform : FilterBase
  {
+ private static class Defaults
+ {
+ public const bool Complement = false;
+ public const bool ShuffleInput = true;
+ public const int PoolSize = 1000;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether this is the out-of-bag sample, that is, all those rows that are not selected by the transform.",
  ShortName = "comp")]
- public bool Complement;
+ public bool Complement = Defaults.Complement;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "The random seed. If unspecified random state will be instead derived from the environment.")]
  public uint? Seed;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.", ShortName = "si")]
- public bool ShuffleInput = true;
+ public bool ShuffleInput = Defaults.ShuffleInput;
 
  [Argument(ArgumentType.LastOccurenceWins, HelpText = "When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.", ShortName = "pool")]
- public int PoolSize = 1000;
+ public int PoolSize = Defaults.PoolSize;
  }
 
  internal const string Summary = "Approximate bootstrap sampling.";
@@ -76,6 +83,25 @@ public BootstrapSampleTransform(IHostEnvironment env, Arguments args, IDataView
  _poolSize = args.PoolSize;
  }
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="complement">Whether this is the out-of-bag sample, that is, all those rows that are not selected by the transform.</param>
+ /// <param name="seed">The random seed. If unspecified random state will be instead derived from the environment.</param>
+ /// <param name="shuffleInput">Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.</param>
+ /// <param name="poolSize">When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.</param>
+ public BootstrapSampleTransform(IHostEnvironment env, 
+ IDataView input, 
+ bool complement = Defaults.Complement, 
+ uint? seed = null, 
+ bool shuffleInput = Defaults.ShuffleInput, 
+ int poolSize = Defaults.PoolSize)
+ : this(env, new Arguments() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
+ {
+ }
+
  private BootstrapSampleTransform(IHost host, ModelLoadContext ctx, IDataView input)
  : base(host, input)
  {

src/Microsoft.ML.Transforms/CategoricalHashTransform.cs

@@ -86,6 +86,15 @@ public bool TryUnparse(StringBuilder sb)
  }
  }
 
+ private static class Defaults
+ {
+ public const int HashBits = 16;
+ public const uint Seed = 314489979;
+ public const bool Ordered = true;
+ public const int InvertHash = 0;
+ public const CategoricalTransform.OutputKind OutputKind = CategoricalTransform.OutputKind.Bag;
+ }
+
  /// <summary>
  /// This class is a merger of <see cref="HashTransform.Arguments"/> and <see cref="KeyToVectorTransform.Arguments"/>
  /// with join option removed
@@ -97,29 +106,61 @@ public sealed class Arguments : TransformInputBase
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Number of bits to hash into. Must be between 1 and 30, inclusive.",
  ShortName = "bits", SortOrder = 2)]
- public int HashBits = 16;
+ public int HashBits = Defaults.HashBits;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Hashing seed")]
- public uint Seed = 314489979;
+ public uint Seed = Defaults.Seed;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether the position of each term should be included in the hash", ShortName = "ord")]
- public bool Ordered = true;
+ public bool Ordered = Defaults.Ordered;
 
  [Argument(ArgumentType.AtMostOnce,
  HelpText = "Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit.",
  ShortName = "ih")]
- public int InvertHash;
+ public int InvertHash = Defaults.InvertHash;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Output kind: Bag (multi-set vector), Ind (indicator vector), or Key (index)",
  ShortName = "kind", SortOrder = 102)]
- public CategoricalTransform.OutputKind OutputKind = CategoricalTransform.OutputKind.Bag;
+ public CategoricalTransform.OutputKind OutputKind = Defaults.OutputKind;
  }
 
  internal const string Summary = "Converts the categorical value into an indicator array by hashing the value and using the hash as an index in the "
  + "bag. If the input column is a vector, a single indicator bag is returned for it.";
 
  public const string UserName = "Categorical Hash Transform";
 
+ /// <summary>
+ /// A helper method to create <see cref="CategoricalHashTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
+ /// <param name="hashBits">Number of bits to hash into. Must be between 1 and 30, inclusive.</param>
+ /// <param name="invertHash">Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit.</param>
+ /// <param name="outputKind">The type of output expected.</param>
+ public static IDataTransform Create(IHostEnvironment env, 
+ IDataView input, 
+ string name, 
+ string source =null, 
+ int hashBits = Defaults.HashBits, 
+ int invertHash = Defaults.InvertHash, 
+ CategoricalTransform.OutputKind outputKind = Defaults.OutputKind)
+ {
+ var args = new Arguments()
+ {
+ Column = new[] { new Column(){
+ Source = source ?? name,
+ Name = name
+ }
+ },
+ HashBits = hashBits,
+ InvertHash = invertHash,
+ OutputKind = outputKind
+ };
+ return Create(env, args, input);
+ }
+
  public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataView input)
  {
  Contracts.CheckValue(env, nameof(env));

src/Microsoft.ML.Transforms/CategoricalTransform.cs

@@ -38,15 +38,27 @@ public static class CategoricalTransform
  {
  public enum OutputKind : byte
  {
+ /// <summary>
+ /// Output is a bag (multi-set) vector
+ /// </summary>
  [TGUI(Label = "Output is a bag (multi-set) vector")]
  Bag = 1,
 
+ /// <summary>
+ /// Output is an indicator vector
+ /// </summary>
  [TGUI(Label = "Output is an indicator vector")]
  Ind = 2,
 
+ /// <summary>
+ /// Output is a key value
+ /// </summary>
  [TGUI(Label = "Output is a key value")]
  Key = 3,
 
+ /// <summary>
+ /// Output is binary encoded
+ /// </summary>
  [TGUI(Label = "Output is binary encoded")]
  Bin = 4,
  }
@@ -96,14 +108,19 @@ public bool TryUnparse(StringBuilder sb)
  }
  }
 
+ private static class Defaults
+ {
+ public const OutputKind OutKind = OutputKind.Ind;
+ }
+
  public sealed class Arguments : TermTransform.ArgumentsBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", ShortName = "col", SortOrder = 1)]
  public Column[] Column;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Output kind: Bag (multi-set vector), Ind (indicator vector), or Key (index)",
  ShortName = "kind", SortOrder = 102)]
- public OutputKind OutputKind = OutputKind.Ind;
+ public OutputKind OutputKind = Defaults.OutKind;
 
  public Arguments()
  {
@@ -118,6 +135,28 @@ public Arguments()
 
  public const string UserName = "Categorical Transform";
 
+ /// <summary>
+ /// A helper method to create <see cref="CategoricalTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
+ /// <param name="outputKind">The type of output expected.</param>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, string name, string source = null, OutputKind outputKind = Defaults.OutKind)
+ {
+ var args = new Arguments()
+ {
+ Column = new[] { new Column(){
+ Source = source ?? name,
+ Name = name
+ }
+ },
+ OutputKind = outputKind
+ };
+ return Create(env, args, input);
+ }
+
  public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataView input)
  {
  Contracts.CheckValue(env, nameof(env));

src/Microsoft.ML.Transforms/CountFeatureSelection.cs

@@ -28,17 +28,40 @@ public static class CountFeatureSelectionTransform
  public const string Summary = "Selects the slots for which the count of non-default values is greater than or equal to a threshold.";
  public const string UserName = "Count Feature Selection Transform";
 
+ private static class Defaults
+ {
+ public const long Count = 1;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Columns to use for feature selection", ShortName = "col", SortOrder = 1)]
  public string[] Column;
 
  [Argument(ArgumentType.Required, HelpText = "If the count of non-default values for a slot is greater than or equal to this threshold, the slot is preserved", ShortName = "c", SortOrder = 1)]
- public long Count = 1;
+ public long Count = Defaults.Count;
  }
 
  internal static string RegistrationName = "CountFeatureSelectionTransform";
 
+ /// <summary>
+ /// A helper method to create CountFeatureSelection transform for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="count">If the count of non-default values for a slot is greater than or equal to this threshold, the slot is preserved.</param>
+ /// <param name="columns">Columns to use for feature selection.</param>
+ /// <returns></returns>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, long count = Defaults.Count, params string[] columns)
+ {
+ var args = new Arguments()
+ {
+ Column = columns,
+ Count = count
+ };
+ return Create(env, args, input);
+ }
+
  /// <summary>
  /// Create method corresponding to SignatureDataTransform.
  /// </summary>

src/Microsoft.ML.Data/Transforms/ConcatTransform.cs

@@ -90,6 +90,19 @@ public bool TryUnparse(StringBuilder sb)
 
  public sealed class Arguments : TransformInputBase
  {
+ public Arguments()
+ {
+ }
+
+ public Arguments(string name, params string[] source)
+ {
+ Column = new[] { new Column()
+ {
+ Name = name,
+ Source = source
+ }};
+ }
+
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:srcs)", ShortName = "col", SortOrder = 1)]
  public Column[] Column;
  }
@@ -527,6 +540,18 @@ private static VersionInfo GetVersionInfo()
 
  public override ISchema Schema => _bindings;
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Input columns to concatenate.</param>
+ public ConcatTransform(IHostEnvironment env, IDataView input, string name, params string[] source)
+ : this(env, new Arguments(name, source), input)
+ {
+ }
+
  /// <summary>
  /// Public constructor corresponding to SignatureDataTransform.
  /// </summary>

src/Microsoft.ML.Data/Transforms/CopyColumnsTransform.cs

@@ -64,6 +64,18 @@ private static VersionInfo GetVersionInfo()
 
  private const string RegistrationName = "CopyColumns";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be copied.</param>
+ public CopyColumnsTransform(IHostEnvironment env, IDataView input, string name, string source)
+ : this(env, new Arguments(){ Column = new[] { new Column() { Source = source, Name = name }}}, input)
+ {
+ }
+
  public CopyColumnsTransform(IHostEnvironment env, Arguments args, IDataView input)
  : base(env, RegistrationName, env.CheckRef(args, nameof(args)).Column, input, null)
  {

src/Microsoft.ML.Data/Transforms/DropColumnsTransform.cs

@@ -237,6 +237,17 @@ private static VersionInfo GetVersionInfo()
  private const string DropRegistrationName = "DropColumns";
  private const string KeepRegistrationName = "KeepColumns";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="columnsToDrop">Name of the columns to be dropped.</param>
+ public DropColumnsTransform(IHostEnvironment env, IDataView input, params string[] columnsToDrop)
+ :this(env, new Arguments() { Column = columnsToDrop }, input)
+ {
+ }
+
  /// <summary>
  /// Public constructor corresponding to SignatureDataTransform.
  /// </summary>
@@ -383,4 +394,17 @@ public ValueGetter<TValue> GetGetter<TValue>(int col)
  }
  }
  }
+
+ public class KeepColumnsTransform
+ {
+ /// <summary>
+ /// A helper method to create <see cref="KeepColumnsTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="columnsToKeep">Name of the columns to be kept. All other columns will be removed.</param>
+ /// <returns></returns>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, params string[] columnsToKeep)
+ => new DropColumnsTransform(env, new DropColumnsTransform.KeepArguments() { Column = columnsToKeep }, input);
+ }
 }

src/Microsoft.ML.Data/Transforms/NAFilter.cs

@@ -28,13 +28,18 @@ namespace Microsoft.ML.Runtime.Data
 {
  public sealed class NAFilter : FilterBase
  {
+ private static class Defaults
+ {
+ public const bool Complement = false;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Column", ShortName = "col", SortOrder = 1)]
  public string[] Column;
 
  [Argument(ArgumentType.Multiple, HelpText = "If true, keep only rows that contain NA values, and filter the rest.")]
- public bool Complement;
+ public bool Complement = Defaults.Complement;
  }
 
  private sealed class ColInfo
@@ -72,6 +77,18 @@ private static VersionInfo GetVersionInfo()
  private readonly bool _complement;
  private const string RegistrationName = "MissingValueFilter";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="complement">If true, keep only rows that contain NA values, and filter the rest.</param>
+ /// <param name="columns">Name of the columns. Only these columns will be used to filter rows having 'NA' values.</param>
+ public NAFilter(IHostEnvironment env, IDataView input, bool complement = Defaults.Complement, params string[] columns)
+ : this(env, new Arguments() { Column = columns, Complement = complement }, input)
+ {
+ }
+
  public NAFilter(IHostEnvironment env, Arguments args, IDataView input)
  : base(env, RegistrationName, input)
  {

src/Microsoft.ML.Transforms/BootstrapSampleTransform.cs

@@ -25,20 +25,27 @@ namespace Microsoft.ML.Runtime.Data
  /// </summary>
  public sealed class BootstrapSampleTransform : FilterBase
  {
+ private static class Defaults
+ {
+ public const bool Complement = false;
+ public const bool ShuffleInput = true;
+ public const int PoolSize = 1000;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether this is the out-of-bag sample, that is, all those rows that are not selected by the transform.",
  ShortName = "comp")]
- public bool Complement;
+ public bool Complement = Defaults.Complement;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "The random seed. If unspecified random state will be instead derived from the environment.")]
  public uint? Seed;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.", ShortName = "si")]
- public bool ShuffleInput = true;
+ public bool ShuffleInput = Defaults.ShuffleInput;
 
  [Argument(ArgumentType.LastOccurenceWins, HelpText = "When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.", ShortName = "pool")]
- public int PoolSize = 1000;
+ public int PoolSize = Defaults.PoolSize;
  }
 
  internal const string Summary = "Approximate bootstrap sampling.";
@@ -76,6 +83,25 @@ public BootstrapSampleTransform(IHostEnvironment env, Arguments args, IDataView
  _poolSize = args.PoolSize;
  }
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="complement">Whether this is the out-of-bag sample, that is, all those rows that are not selected by the transform.</param>
+ /// <param name="seed">The random seed. If unspecified random state will be instead derived from the environment.</param>
+ /// <param name="shuffleInput">Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.</param>
+ /// <param name="poolSize">When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.</param>
+ public BootstrapSampleTransform(IHostEnvironment env, 
+ IDataView input, 
+ bool complement = Defaults.Complement, 
+ uint? seed = null, 
+ bool shuffleInput = Defaults.ShuffleInput, 
+ int poolSize = Defaults.PoolSize)
+ : this(env, new Arguments() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
+ {
+ }
+
  private BootstrapSampleTransform(IHost host, ModelLoadContext ctx, IDataView input)
  : base(host, input)
  {

src/Microsoft.ML.Transforms/CategoricalHashTransform.cs

@@ -86,6 +86,15 @@ public bool TryUnparse(StringBuilder sb)
  }
  }
 
+ private static class Defaults
+ {
+ public const int HashBits = 16;
+ public const uint Seed = 314489979;
+ public const bool Ordered = true;
+ public const int InvertHash = 0;
+ public const CategoricalTransform.OutputKind OutputKind = CategoricalTransform.OutputKind.Bag;
+ }
+
  /// <summary>
  /// This class is a merger of <see cref="HashTransform.Arguments"/> and <see cref="KeyToVectorTransform.Arguments"/>
  /// with join option removed
@@ -97,29 +106,61 @@ public sealed class Arguments : TransformInputBase
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Number of bits to hash into. Must be between 1 and 30, inclusive.",
  ShortName = "bits", SortOrder = 2)]
- public int HashBits = 16;
+ public int HashBits = Defaults.HashBits;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Hashing seed")]
- public uint Seed = 314489979;
+ public uint Seed = Defaults.Seed;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether the position of each term should be included in the hash", ShortName = "ord")]
- public bool Ordered = true;
+ public bool Ordered = Defaults.Ordered;
 
  [Argument(ArgumentType.AtMostOnce,
  HelpText = "Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit.",
  ShortName = "ih")]
- public int InvertHash;
+ public int InvertHash = Defaults.InvertHash;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Output kind: Bag (multi-set vector), Ind (indicator vector), or Key (index)",
  ShortName = "kind", SortOrder = 102)]
- public CategoricalTransform.OutputKind OutputKind = CategoricalTransform.OutputKind.Bag;
+ public CategoricalTransform.OutputKind OutputKind = Defaults.OutputKind;
  }
 
  internal const string Summary = "Converts the categorical value into an indicator array by hashing the value and using the hash as an index in the "
  + "bag. If the input column is a vector, a single indicator bag is returned for it.";
 
  public const string UserName = "Categorical Hash Transform";
 
+ /// <summary>
+ /// A helper method to create <see cref="CategoricalHashTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
+ /// <param name="hashBits">Number of bits to hash into. Must be between 1 and 30, inclusive.</param>
+ /// <param name="invertHash">Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit.</param>
+ /// <param name="outputKind">The type of output expected.</param>
+ public static IDataTransform Create(IHostEnvironment env, 
+ IDataView input, 
+ string name, 
+ string source =null, 
+ int hashBits = Defaults.HashBits, 
+ int invertHash = Defaults.InvertHash, 
+ CategoricalTransform.OutputKind outputKind = Defaults.OutputKind)
+ {
+ var args = new Arguments()
+ {
+ Column = new[] { new Column(){
+ Source = source ?? name,
+ Name = name
+ }
+ },
+ HashBits = hashBits,
+ InvertHash = invertHash,
+ OutputKind = outputKind
+ };
+ return Create(env, args, input);
+ }
+
  public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataView input)
  {
  Contracts.CheckValue(env, nameof(env));

src/Microsoft.ML.Transforms/CategoricalTransform.cs

@@ -38,15 +38,27 @@ public static class CategoricalTransform
  {
  public enum OutputKind : byte
  {
+ /// <summary>
+ /// Output is a bag (multi-set) vector
+ /// </summary>
  [TGUI(Label = "Output is a bag (multi-set) vector")]
  Bag = 1,
 
+ /// <summary>
+ /// Output is an indicator vector
+ /// </summary>
  [TGUI(Label = "Output is an indicator vector")]
  Ind = 2,
 
+ /// <summary>
+ /// Output is a key value
+ /// </summary>
  [TGUI(Label = "Output is a key value")]
  Key = 3,
 
+ /// <summary>
+ /// Output is binary encoded
+ /// </summary>
  [TGUI(Label = "Output is binary encoded")]
  Bin = 4,
  }
@@ -96,14 +108,19 @@ public bool TryUnparse(StringBuilder sb)
  }
  }
 
+ private static class Defaults
+ {
+ public const OutputKind OutKind = OutputKind.Ind;
+ }
+
  public sealed class Arguments : TermTransform.ArgumentsBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", ShortName = "col", SortOrder = 1)]
  public Column[] Column;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Output kind: Bag (multi-set vector), Ind (indicator vector), or Key (index)",
  ShortName = "kind", SortOrder = 102)]
- public OutputKind OutputKind = OutputKind.Ind;
+ public OutputKind OutputKind = Defaults.OutKind;
 
  public Arguments()
  {
@@ -118,6 +135,28 @@ public Arguments()
 
  public const string UserName = "Categorical Transform";
 
+ /// <summary>
+ /// A helper method to create <see cref="CategoricalTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
+ /// <param name="outputKind">The type of output expected.</param>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, string name, string source = null, OutputKind outputKind = Defaults.OutKind)
+ {
+ var args = new Arguments()
+ {
+ Column = new[] { new Column(){
+ Source = source ?? name,
+ Name = name
+ }
+ },
+ OutputKind = outputKind
+ };
+ return Create(env, args, input);
+ }
+
  public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataView input)
  {
  Contracts.CheckValue(env, nameof(env));

src/Microsoft.ML.Transforms/CountFeatureSelection.cs

@@ -28,17 +28,40 @@ public static class CountFeatureSelectionTransform
  public const string Summary = "Selects the slots for which the count of non-default values is greater than or equal to a threshold.";
  public const string UserName = "Count Feature Selection Transform";
 
+ private static class Defaults
+ {
+ public const long Count = 1;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Columns to use for feature selection", ShortName = "col", SortOrder = 1)]
  public string[] Column;
 
  [Argument(ArgumentType.Required, HelpText = "If the count of non-default values for a slot is greater than or equal to this threshold, the slot is preserved", ShortName = "c", SortOrder = 1)]
- public long Count = 1;
+ public long Count = Defaults.Count;
  }
 
  internal static string RegistrationName = "CountFeatureSelectionTransform";
 
+ /// <summary>
+ /// A helper method to create CountFeatureSelection transform for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="count">If the count of non-default values for a slot is greater than or equal to this threshold, the slot is preserved.</param>
+ /// <param name="columns">Columns to use for feature selection.</param>
+ /// <returns></returns>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, long count = Defaults.Count, params string[] columns)
+ {
+ var args = new Arguments()
+ {
+ Column = columns,
+ Count = count
+ };
+ return Create(env, args, input);
+ }
+
  /// <summary>
  /// Create method corresponding to SignatureDataTransform.
  /// </summary>

src/Microsoft.ML.Data/Transforms/ConcatTransform.cs

@@ -90,6 +90,19 @@ public bool TryUnparse(StringBuilder sb)
 
  public sealed class Arguments : TransformInputBase
  {
+ public Arguments()
+ {
+ }
+
+ public Arguments(string name, params string[] source)
+ {
+ Column = new[] { new Column()
+ {
+ Name = name,
+ Source = source
+ }};
+ }
+
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:srcs)", ShortName = "col", SortOrder = 1)]
  public Column[] Column;
  }
@@ -527,6 +540,18 @@ private static VersionInfo GetVersionInfo()
 
  public override ISchema Schema => _bindings;
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Input columns to concatenate.</param>
+ public ConcatTransform(IHostEnvironment env, IDataView input, string name, params string[] source)
+ : this(env, new Arguments(name, source), input)
+ {
+ }
+
  /// <summary>
  /// Public constructor corresponding to SignatureDataTransform.
  /// </summary>

src/Microsoft.ML.Data/Transforms/CopyColumnsTransform.cs

@@ -64,6 +64,18 @@ private static VersionInfo GetVersionInfo()
 
  private const string RegistrationName = "CopyColumns";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be copied.</param>
+ public CopyColumnsTransform(IHostEnvironment env, IDataView input, string name, string source)
+ : this(env, new Arguments(){ Column = new[] { new Column() { Source = source, Name = name }}}, input)
+ {
+ }
+
  public CopyColumnsTransform(IHostEnvironment env, Arguments args, IDataView input)
  : base(env, RegistrationName, env.CheckRef(args, nameof(args)).Column, input, null)
  {

src/Microsoft.ML.Data/Transforms/DropColumnsTransform.cs

@@ -237,6 +237,17 @@ private static VersionInfo GetVersionInfo()
  private const string DropRegistrationName = "DropColumns";
  private const string KeepRegistrationName = "KeepColumns";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="columnsToDrop">Name of the columns to be dropped.</param>
+ public DropColumnsTransform(IHostEnvironment env, IDataView input, params string[] columnsToDrop)
+ :this(env, new Arguments() { Column = columnsToDrop }, input)
+ {
+ }
+
  /// <summary>
  /// Public constructor corresponding to SignatureDataTransform.
  /// </summary>
@@ -383,4 +394,17 @@ public ValueGetter<TValue> GetGetter<TValue>(int col)
  }
  }
  }
+
+ public class KeepColumnsTransform
+ {
+ /// <summary>
+ /// A helper method to create <see cref="KeepColumnsTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="columnsToKeep">Name of the columns to be kept. All other columns will be removed.</param>
+ /// <returns></returns>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, params string[] columnsToKeep)
+ => new DropColumnsTransform(env, new DropColumnsTransform.KeepArguments() { Column = columnsToKeep }, input);
+ }
 }

src/Microsoft.ML.Data/Transforms/NAFilter.cs

@@ -28,13 +28,18 @@ namespace Microsoft.ML.Runtime.Data
 {
  public sealed class NAFilter : FilterBase
  {
+ private static class Defaults
+ {
+ public const bool Complement = false;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Column", ShortName = "col", SortOrder = 1)]
  public string[] Column;
 
  [Argument(ArgumentType.Multiple, HelpText = "If true, keep only rows that contain NA values, and filter the rest.")]
- public bool Complement;
+ public bool Complement = Defaults.Complement;
  }
 
  private sealed class ColInfo
@@ -72,6 +77,18 @@ private static VersionInfo GetVersionInfo()
  private readonly bool _complement;
  private const string RegistrationName = "MissingValueFilter";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="complement">If true, keep only rows that contain NA values, and filter the rest.</param>
+ /// <param name="columns">Name of the columns. Only these columns will be used to filter rows having 'NA' values.</param>
+ public NAFilter(IHostEnvironment env, IDataView input, bool complement = Defaults.Complement, params string[] columns)
+ : this(env, new Arguments() { Column = columns, Complement = complement }, input)
+ {
+ }
+
  public NAFilter(IHostEnvironment env, Arguments args, IDataView input)
  : base(env, RegistrationName, input)
  {

src/Microsoft.ML.Transforms/BootstrapSampleTransform.cs

@@ -25,20 +25,27 @@ namespace Microsoft.ML.Runtime.Data
  /// </summary>
  public sealed class BootstrapSampleTransform : FilterBase
  {
+ private static class Defaults
+ {
+ public const bool Complement = false;
+ public const bool ShuffleInput = true;
+ public const int PoolSize = 1000;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether this is the out-of-bag sample, that is, all those rows that are not selected by the transform.",
  ShortName = "comp")]
- public bool Complement;
+ public bool Complement = Defaults.Complement;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "The random seed. If unspecified random state will be instead derived from the environment.")]
  public uint? Seed;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.", ShortName = "si")]
- public bool ShuffleInput = true;
+ public bool ShuffleInput = Defaults.ShuffleInput;
 
  [Argument(ArgumentType.LastOccurenceWins, HelpText = "When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.", ShortName = "pool")]
- public int PoolSize = 1000;
+ public int PoolSize = Defaults.PoolSize;
  }
 
  internal const string Summary = "Approximate bootstrap sampling.";
@@ -76,6 +83,25 @@ public BootstrapSampleTransform(IHostEnvironment env, Arguments args, IDataView
  _poolSize = args.PoolSize;
  }
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="complement">Whether this is the out-of-bag sample, that is, all those rows that are not selected by the transform.</param>
+ /// <param name="seed">The random seed. If unspecified random state will be instead derived from the environment.</param>
+ /// <param name="shuffleInput">Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.</param>
+ /// <param name="poolSize">When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.</param>
+ public BootstrapSampleTransform(IHostEnvironment env, 
+ IDataView input, 
+ bool complement = Defaults.Complement, 
+ uint? seed = null, 
+ bool shuffleInput = Defaults.ShuffleInput, 
+ int poolSize = Defaults.PoolSize)
+ : this(env, new Arguments() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
+ {
+ }
+
  private BootstrapSampleTransform(IHost host, ModelLoadContext ctx, IDataView input)
  : base(host, input)
  {

src/Microsoft.ML.Transforms/CategoricalHashTransform.cs

@@ -86,6 +86,15 @@ public bool TryUnparse(StringBuilder sb)
  }
  }
 
+ private static class Defaults
+ {
+ public const int HashBits = 16;
+ public const uint Seed = 314489979;
+ public const bool Ordered = true;
+ public const int InvertHash = 0;
+ public const CategoricalTransform.OutputKind OutputKind = CategoricalTransform.OutputKind.Bag;
+ }
+
  /// <summary>
  /// This class is a merger of <see cref="HashTransform.Arguments"/> and <see cref="KeyToVectorTransform.Arguments"/>
  /// with join option removed
@@ -97,29 +106,61 @@ public sealed class Arguments : TransformInputBase
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Number of bits to hash into. Must be between 1 and 30, inclusive.",
  ShortName = "bits", SortOrder = 2)]
- public int HashBits = 16;
+ public int HashBits = Defaults.HashBits;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Hashing seed")]
- public uint Seed = 314489979;
+ public uint Seed = Defaults.Seed;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether the position of each term should be included in the hash", ShortName = "ord")]
- public bool Ordered = true;
+ public bool Ordered = Defaults.Ordered;
 
  [Argument(ArgumentType.AtMostOnce,
  HelpText = "Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit.",
  ShortName = "ih")]
- public int InvertHash;
+ public int InvertHash = Defaults.InvertHash;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Output kind: Bag (multi-set vector), Ind (indicator vector), or Key (index)",
  ShortName = "kind", SortOrder = 102)]
- public CategoricalTransform.OutputKind OutputKind = CategoricalTransform.OutputKind.Bag;
+ public CategoricalTransform.OutputKind OutputKind = Defaults.OutputKind;
  }
 
  internal const string Summary = "Converts the categorical value into an indicator array by hashing the value and using the hash as an index in the "
  + "bag. If the input column is a vector, a single indicator bag is returned for it.";
 
  public const string UserName = "Categorical Hash Transform";
 
+ /// <summary>
+ /// A helper method to create <see cref="CategoricalHashTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
+ /// <param name="hashBits">Number of bits to hash into. Must be between 1 and 30, inclusive.</param>
+ /// <param name="invertHash">Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit.</param>
+ /// <param name="outputKind">The type of output expected.</param>
+ public static IDataTransform Create(IHostEnvironment env, 
+ IDataView input, 
+ string name, 
+ string source =null, 
+ int hashBits = Defaults.HashBits, 
+ int invertHash = Defaults.InvertHash, 
+ CategoricalTransform.OutputKind outputKind = Defaults.OutputKind)
+ {
+ var args = new Arguments()
+ {
+ Column = new[] { new Column(){
+ Source = source ?? name,
+ Name = name
+ }
+ },
+ HashBits = hashBits,
+ InvertHash = invertHash,
+ OutputKind = outputKind
+ };
+ return Create(env, args, input);
+ }
+
  public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataView input)
  {
  Contracts.CheckValue(env, nameof(env));

src/Microsoft.ML.Transforms/CategoricalTransform.cs

@@ -38,15 +38,27 @@ public static class CategoricalTransform
  {
  public enum OutputKind : byte
  {
+ /// <summary>
+ /// Output is a bag (multi-set) vector
+ /// </summary>
  [TGUI(Label = "Output is a bag (multi-set) vector")]
  Bag = 1,
 
+ /// <summary>
+ /// Output is an indicator vector
+ /// </summary>
  [TGUI(Label = "Output is an indicator vector")]
  Ind = 2,
 
+ /// <summary>
+ /// Output is a key value
+ /// </summary>
  [TGUI(Label = "Output is a key value")]
  Key = 3,
 
+ /// <summary>
+ /// Output is binary encoded
+ /// </summary>
  [TGUI(Label = "Output is binary encoded")]
  Bin = 4,
  }
@@ -96,14 +108,19 @@ public bool TryUnparse(StringBuilder sb)
  }
  }
 
+ private static class Defaults
+ {
+ public const OutputKind OutKind = OutputKind.Ind;
+ }
+
  public sealed class Arguments : TermTransform.ArgumentsBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", ShortName = "col", SortOrder = 1)]
  public Column[] Column;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Output kind: Bag (multi-set vector), Ind (indicator vector), or Key (index)",
  ShortName = "kind", SortOrder = 102)]
- public OutputKind OutputKind = OutputKind.Ind;
+ public OutputKind OutputKind = Defaults.OutKind;
 
  public Arguments()
  {
@@ -118,6 +135,28 @@ public Arguments()
 
  public const string UserName = "Categorical Transform";
 
+ /// <summary>
+ /// A helper method to create <see cref="CategoricalTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
+ /// <param name="outputKind">The type of output expected.</param>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, string name, string source = null, OutputKind outputKind = Defaults.OutKind)
+ {
+ var args = new Arguments()
+ {
+ Column = new[] { new Column(){
+ Source = source ?? name,
+ Name = name
+ }
+ },
+ OutputKind = outputKind
+ };
+ return Create(env, args, input);
+ }
+
  public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataView input)
  {
  Contracts.CheckValue(env, nameof(env));

src/Microsoft.ML.Transforms/CountFeatureSelection.cs

@@ -28,17 +28,40 @@ public static class CountFeatureSelectionTransform
  public const string Summary = "Selects the slots for which the count of non-default values is greater than or equal to a threshold.";
  public const string UserName = "Count Feature Selection Transform";
 
+ private static class Defaults
+ {
+ public const long Count = 1;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Columns to use for feature selection", ShortName = "col", SortOrder = 1)]
  public string[] Column;
 
  [Argument(ArgumentType.Required, HelpText = "If the count of non-default values for a slot is greater than or equal to this threshold, the slot is preserved", ShortName = "c", SortOrder = 1)]
- public long Count = 1;
+ public long Count = Defaults.Count;
  }
 
  internal static string RegistrationName = "CountFeatureSelectionTransform";
 
+ /// <summary>
+ /// A helper method to create CountFeatureSelection transform for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="count">If the count of non-default values for a slot is greater than or equal to this threshold, the slot is preserved.</param>
+ /// <param name="columns">Columns to use for feature selection.</param>
+ /// <returns></returns>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, long count = Defaults.Count, params string[] columns)
+ {
+ var args = new Arguments()
+ {
+ Column = columns,
+ Count = count
+ };
+ return Create(env, args, input);
+ }
+
  /// <summary>
  /// Create method corresponding to SignatureDataTransform.
  /// </summary>

src/Microsoft.ML.Data/Transforms/ConcatTransform.cs

@@ -90,6 +90,19 @@ public bool TryUnparse(StringBuilder sb)
 
  public sealed class Arguments : TransformInputBase
  {
+ public Arguments()
+ {
+ }
+
+ public Arguments(string name, params string[] source)
+ {
+ Column = new[] { new Column()
+ {
+ Name = name,
+ Source = source
+ }};
+ }
+
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:srcs)", ShortName = "col", SortOrder = 1)]
  public Column[] Column;
  }
@@ -527,6 +540,18 @@ private static VersionInfo GetVersionInfo()
 
  public override ISchema Schema => _bindings;
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Input columns to concatenate.</param>
+ public ConcatTransform(IHostEnvironment env, IDataView input, string name, params string[] source)
+ : this(env, new Arguments(name, source), input)
+ {
+ }
+
  /// <summary>
  /// Public constructor corresponding to SignatureDataTransform.
  /// </summary>

src/Microsoft.ML.Data/Transforms/CopyColumnsTransform.cs

@@ -64,6 +64,18 @@ private static VersionInfo GetVersionInfo()
 
  private const string RegistrationName = "CopyColumns";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be copied.</param>
+ public CopyColumnsTransform(IHostEnvironment env, IDataView input, string name, string source)
+ : this(env, new Arguments(){ Column = new[] { new Column() { Source = source, Name = name }}}, input)
+ {
+ }
+
  public CopyColumnsTransform(IHostEnvironment env, Arguments args, IDataView input)
  : base(env, RegistrationName, env.CheckRef(args, nameof(args)).Column, input, null)
  {

src/Microsoft.ML.Data/Transforms/DropColumnsTransform.cs

@@ -237,6 +237,17 @@ private static VersionInfo GetVersionInfo()
  private const string DropRegistrationName = "DropColumns";
  private const string KeepRegistrationName = "KeepColumns";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="columnsToDrop">Name of the columns to be dropped.</param>
+ public DropColumnsTransform(IHostEnvironment env, IDataView input, params string[] columnsToDrop)
+ :this(env, new Arguments() { Column = columnsToDrop }, input)
+ {
+ }
+
  /// <summary>
  /// Public constructor corresponding to SignatureDataTransform.
  /// </summary>
@@ -383,4 +394,17 @@ public ValueGetter<TValue> GetGetter<TValue>(int col)
  }
  }
  }
+
+ public class KeepColumnsTransform
+ {
+ /// <summary>
+ /// A helper method to create <see cref="KeepColumnsTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="columnsToKeep">Name of the columns to be kept. All other columns will be removed.</param>
+ /// <returns></returns>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, params string[] columnsToKeep)
+ => new DropColumnsTransform(env, new DropColumnsTransform.KeepArguments() { Column = columnsToKeep }, input);
+ }
 }

src/Microsoft.ML.Data/Transforms/NAFilter.cs

@@ -28,13 +28,18 @@ namespace Microsoft.ML.Runtime.Data
 {
  public sealed class NAFilter : FilterBase
  {
+ private static class Defaults
+ {
+ public const bool Complement = false;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Column", ShortName = "col", SortOrder = 1)]
  public string[] Column;
 
  [Argument(ArgumentType.Multiple, HelpText = "If true, keep only rows that contain NA values, and filter the rest.")]
- public bool Complement;
+ public bool Complement = Defaults.Complement;
  }
 
  private sealed class ColInfo
@@ -72,6 +77,18 @@ private static VersionInfo GetVersionInfo()
  private readonly bool _complement;
  private const string RegistrationName = "MissingValueFilter";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="complement">If true, keep only rows that contain NA values, and filter the rest.</param>
+ /// <param name="columns">Name of the columns. Only these columns will be used to filter rows having 'NA' values.</param>
+ public NAFilter(IHostEnvironment env, IDataView input, bool complement = Defaults.Complement, params string[] columns)
+ : this(env, new Arguments() { Column = columns, Complement = complement }, input)
+ {
+ }
+
  public NAFilter(IHostEnvironment env, Arguments args, IDataView input)
  : base(env, RegistrationName, input)
  {

src/Microsoft.ML.Transforms/BootstrapSampleTransform.cs

@@ -25,20 +25,27 @@ namespace Microsoft.ML.Runtime.Data
  /// </summary>
  public sealed class BootstrapSampleTransform : FilterBase
  {
+ private static class Defaults
+ {
+ public const bool Complement = false;
+ public const bool ShuffleInput = true;
+ public const int PoolSize = 1000;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether this is the out-of-bag sample, that is, all those rows that are not selected by the transform.",
  ShortName = "comp")]
- public bool Complement;
+ public bool Complement = Defaults.Complement;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "The random seed. If unspecified random state will be instead derived from the environment.")]
  public uint? Seed;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.", ShortName = "si")]
- public bool ShuffleInput = true;
+ public bool ShuffleInput = Defaults.ShuffleInput;
 
  [Argument(ArgumentType.LastOccurenceWins, HelpText = "When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.", ShortName = "pool")]
- public int PoolSize = 1000;
+ public int PoolSize = Defaults.PoolSize;
  }
 
  internal const string Summary = "Approximate bootstrap sampling.";
@@ -76,6 +83,25 @@ public BootstrapSampleTransform(IHostEnvironment env, Arguments args, IDataView
  _poolSize = args.PoolSize;
  }
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="complement">Whether this is the out-of-bag sample, that is, all those rows that are not selected by the transform.</param>
+ /// <param name="seed">The random seed. If unspecified random state will be instead derived from the environment.</param>
+ /// <param name="shuffleInput">Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.</param>
+ /// <param name="poolSize">When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.</param>
+ public BootstrapSampleTransform(IHostEnvironment env, 
+ IDataView input, 
+ bool complement = Defaults.Complement, 
+ uint? seed = null, 
+ bool shuffleInput = Defaults.ShuffleInput, 
+ int poolSize = Defaults.PoolSize)
+ : this(env, new Arguments() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
+ {
+ }
+
  private BootstrapSampleTransform(IHost host, ModelLoadContext ctx, IDataView input)
  : base(host, input)
  {

src/Microsoft.ML.Transforms/CategoricalHashTransform.cs

@@ -86,6 +86,15 @@ public bool TryUnparse(StringBuilder sb)
  }
  }
 
+ private static class Defaults
+ {
+ public const int HashBits = 16;
+ public const uint Seed = 314489979;
+ public const bool Ordered = true;
+ public const int InvertHash = 0;
+ public const CategoricalTransform.OutputKind OutputKind = CategoricalTransform.OutputKind.Bag;
+ }
+
  /// <summary>
  /// This class is a merger of <see cref="HashTransform.Arguments"/> and <see cref="KeyToVectorTransform.Arguments"/>
  /// with join option removed
@@ -97,29 +106,61 @@ public sealed class Arguments : TransformInputBase
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Number of bits to hash into. Must be between 1 and 30, inclusive.",
  ShortName = "bits", SortOrder = 2)]
- public int HashBits = 16;
+ public int HashBits = Defaults.HashBits;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Hashing seed")]
- public uint Seed = 314489979;
+ public uint Seed = Defaults.Seed;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether the position of each term should be included in the hash", ShortName = "ord")]
- public bool Ordered = true;
+ public bool Ordered = Defaults.Ordered;
 
  [Argument(ArgumentType.AtMostOnce,
  HelpText = "Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit.",
  ShortName = "ih")]
- public int InvertHash;
+ public int InvertHash = Defaults.InvertHash;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Output kind: Bag (multi-set vector), Ind (indicator vector), or Key (index)",
  ShortName = "kind", SortOrder = 102)]
- public CategoricalTransform.OutputKind OutputKind = CategoricalTransform.OutputKind.Bag;
+ public CategoricalTransform.OutputKind OutputKind = Defaults.OutputKind;
  }
 
  internal const string Summary = "Converts the categorical value into an indicator array by hashing the value and using the hash as an index in the "
  + "bag. If the input column is a vector, a single indicator bag is returned for it.";
 
  public const string UserName = "Categorical Hash Transform";
 
+ /// <summary>
+ /// A helper method to create <see cref="CategoricalHashTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
+ /// <param name="hashBits">Number of bits to hash into. Must be between 1 and 30, inclusive.</param>
+ /// <param name="invertHash">Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit.</param>
+ /// <param name="outputKind">The type of output expected.</param>
+ public static IDataTransform Create(IHostEnvironment env, 
+ IDataView input, 
+ string name, 
+ string source =null, 
+ int hashBits = Defaults.HashBits, 
+ int invertHash = Defaults.InvertHash, 
+ CategoricalTransform.OutputKind outputKind = Defaults.OutputKind)
+ {
+ var args = new Arguments()
+ {
+ Column = new[] { new Column(){
+ Source = source ?? name,
+ Name = name
+ }
+ },
+ HashBits = hashBits,
+ InvertHash = invertHash,
+ OutputKind = outputKind
+ };
+ return Create(env, args, input);
+ }
+
  public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataView input)
  {
  Contracts.CheckValue(env, nameof(env));

src/Microsoft.ML.Transforms/CategoricalTransform.cs

@@ -38,15 +38,27 @@ public static class CategoricalTransform
  {
  public enum OutputKind : byte
  {
+ /// <summary>
+ /// Output is a bag (multi-set) vector
+ /// </summary>
  [TGUI(Label = "Output is a bag (multi-set) vector")]
  Bag = 1,
 
+ /// <summary>
+ /// Output is an indicator vector
+ /// </summary>
  [TGUI(Label = "Output is an indicator vector")]
  Ind = 2,
 
+ /// <summary>
+ /// Output is a key value
+ /// </summary>
  [TGUI(Label = "Output is a key value")]
  Key = 3,
 
+ /// <summary>
+ /// Output is binary encoded
+ /// </summary>
  [TGUI(Label = "Output is binary encoded")]
  Bin = 4,
  }
@@ -96,14 +108,19 @@ public bool TryUnparse(StringBuilder sb)
  }
  }
 
+ private static class Defaults
+ {
+ public const OutputKind OutKind = OutputKind.Ind;
+ }
+
  public sealed class Arguments : TermTransform.ArgumentsBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", ShortName = "col", SortOrder = 1)]
  public Column[] Column;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Output kind: Bag (multi-set vector), Ind (indicator vector), or Key (index)",
  ShortName = "kind", SortOrder = 102)]
- public OutputKind OutputKind = OutputKind.Ind;
+ public OutputKind OutputKind = Defaults.OutKind;
 
  public Arguments()
  {
@@ -118,6 +135,28 @@ public Arguments()
 
  public const string UserName = "Categorical Transform";
 
+ /// <summary>
+ /// A helper method to create <see cref="CategoricalTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
+ /// <param name="outputKind">The type of output expected.</param>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, string name, string source = null, OutputKind outputKind = Defaults.OutKind)
+ {
+ var args = new Arguments()
+ {
+ Column = new[] { new Column(){
+ Source = source ?? name,
+ Name = name
+ }
+ },
+ OutputKind = outputKind
+ };
+ return Create(env, args, input);
+ }
+
  public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataView input)
  {
  Contracts.CheckValue(env, nameof(env));

src/Microsoft.ML.Transforms/CountFeatureSelection.cs

@@ -28,17 +28,40 @@ public static class CountFeatureSelectionTransform
  public const string Summary = "Selects the slots for which the count of non-default values is greater than or equal to a threshold.";
  public const string UserName = "Count Feature Selection Transform";
 
+ private static class Defaults
+ {
+ public const long Count = 1;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Columns to use for feature selection", ShortName = "col", SortOrder = 1)]
  public string[] Column;
 
  [Argument(ArgumentType.Required, HelpText = "If the count of non-default values for a slot is greater than or equal to this threshold, the slot is preserved", ShortName = "c", SortOrder = 1)]
- public long Count = 1;
+ public long Count = Defaults.Count;
  }
 
  internal static string RegistrationName = "CountFeatureSelectionTransform";
 
+ /// <summary>
+ /// A helper method to create CountFeatureSelection transform for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="count">If the count of non-default values for a slot is greater than or equal to this threshold, the slot is preserved.</param>
+ /// <param name="columns">Columns to use for feature selection.</param>
+ /// <returns></returns>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, long count = Defaults.Count, params string[] columns)
+ {
+ var args = new Arguments()
+ {
+ Column = columns,
+ Count = count
+ };
+ return Create(env, args, input);
+ }
+
  /// <summary>
  /// Create method corresponding to SignatureDataTransform.
  /// </summary>

src/Microsoft.ML.Data/Transforms/ConcatTransform.cs

@@ -90,6 +90,19 @@ public bool TryUnparse(StringBuilder sb)
 
  public sealed class Arguments : TransformInputBase
  {
+ public Arguments()
+ {
+ }
+
+ public Arguments(string name, params string[] source)
+ {
+ Column = new[] { new Column()
+ {
+ Name = name,
+ Source = source
+ }};
+ }
+
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:srcs)", ShortName = "col", SortOrder = 1)]
  public Column[] Column;
  }
@@ -527,6 +540,18 @@ private static VersionInfo GetVersionInfo()
 
  public override ISchema Schema => _bindings;
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Input columns to concatenate.</param>
+ public ConcatTransform(IHostEnvironment env, IDataView input, string name, params string[] source)
+ : this(env, new Arguments(name, source), input)
+ {
+ }
+
  /// <summary>
  /// Public constructor corresponding to SignatureDataTransform.
  /// </summary>

src/Microsoft.ML.Data/Transforms/CopyColumnsTransform.cs

@@ -64,6 +64,18 @@ private static VersionInfo GetVersionInfo()
 
  private const string RegistrationName = "CopyColumns";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be copied.</param>
+ public CopyColumnsTransform(IHostEnvironment env, IDataView input, string name, string source)
+ : this(env, new Arguments(){ Column = new[] { new Column() { Source = source, Name = name }}}, input)
+ {
+ }
+
  public CopyColumnsTransform(IHostEnvironment env, Arguments args, IDataView input)
  : base(env, RegistrationName, env.CheckRef(args, nameof(args)).Column, input, null)
  {

src/Microsoft.ML.Data/Transforms/DropColumnsTransform.cs

@@ -237,6 +237,17 @@ private static VersionInfo GetVersionInfo()
  private const string DropRegistrationName = "DropColumns";
  private const string KeepRegistrationName = "KeepColumns";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="columnsToDrop">Name of the columns to be dropped.</param>
+ public DropColumnsTransform(IHostEnvironment env, IDataView input, params string[] columnsToDrop)
+ :this(env, new Arguments() { Column = columnsToDrop }, input)
+ {
+ }
+
  /// <summary>
  /// Public constructor corresponding to SignatureDataTransform.
  /// </summary>
@@ -383,4 +394,17 @@ public ValueGetter<TValue> GetGetter<TValue>(int col)
  }
  }
  }
+
+ public class KeepColumnsTransform
+ {
+ /// <summary>
+ /// A helper method to create <see cref="KeepColumnsTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="columnsToKeep">Name of the columns to be kept. All other columns will be removed.</param>
+ /// <returns></returns>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, params string[] columnsToKeep)
+ => new DropColumnsTransform(env, new DropColumnsTransform.KeepArguments() { Column = columnsToKeep }, input);
+ }
 }

src/Microsoft.ML.Data/Transforms/NAFilter.cs

@@ -28,13 +28,18 @@ namespace Microsoft.ML.Runtime.Data
 {
  public sealed class NAFilter : FilterBase
  {
+ private static class Defaults
+ {
+ public const bool Complement = false;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Column", ShortName = "col", SortOrder = 1)]
  public string[] Column;
 
  [Argument(ArgumentType.Multiple, HelpText = "If true, keep only rows that contain NA values, and filter the rest.")]
- public bool Complement;
+ public bool Complement = Defaults.Complement;
  }
 
  private sealed class ColInfo
@@ -72,6 +77,18 @@ private static VersionInfo GetVersionInfo()
  private readonly bool _complement;
  private const string RegistrationName = "MissingValueFilter";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="complement">If true, keep only rows that contain NA values, and filter the rest.</param>
+ /// <param name="columns">Name of the columns. Only these columns will be used to filter rows having 'NA' values.</param>
+ public NAFilter(IHostEnvironment env, IDataView input, bool complement = Defaults.Complement, params string[] columns)
+ : this(env, new Arguments() { Column = columns, Complement = complement }, input)
+ {
+ }
+
  public NAFilter(IHostEnvironment env, Arguments args, IDataView input)
  : base(env, RegistrationName, input)
  {

src/Microsoft.ML.Transforms/BootstrapSampleTransform.cs

@@ -25,20 +25,27 @@ namespace Microsoft.ML.Runtime.Data
  /// </summary>
  public sealed class BootstrapSampleTransform : FilterBase
  {
+ private static class Defaults
+ {
+ public const bool Complement = false;
+ public const bool ShuffleInput = true;
+ public const int PoolSize = 1000;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether this is the out-of-bag sample, that is, all those rows that are not selected by the transform.",
  ShortName = "comp")]
- public bool Complement;
+ public bool Complement = Defaults.Complement;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "The random seed. If unspecified random state will be instead derived from the environment.")]
  public uint? Seed;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.", ShortName = "si")]
- public bool ShuffleInput = true;
+ public bool ShuffleInput = Defaults.ShuffleInput;
 
  [Argument(ArgumentType.LastOccurenceWins, HelpText = "When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.", ShortName = "pool")]
- public int PoolSize = 1000;
+ public int PoolSize = Defaults.PoolSize;
  }
 
  internal const string Summary = "Approximate bootstrap sampling.";
@@ -76,6 +83,25 @@ public BootstrapSampleTransform(IHostEnvironment env, Arguments args, IDataView
  _poolSize = args.PoolSize;
  }
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="complement">Whether this is the out-of-bag sample, that is, all those rows that are not selected by the transform.</param>
+ /// <param name="seed">The random seed. If unspecified random state will be instead derived from the environment.</param>
+ /// <param name="shuffleInput">Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.</param>
+ /// <param name="poolSize">When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.</param>
+ public BootstrapSampleTransform(IHostEnvironment env, 
+ IDataView input, 
+ bool complement = Defaults.Complement, 
+ uint? seed = null, 
+ bool shuffleInput = Defaults.ShuffleInput, 
+ int poolSize = Defaults.PoolSize)
+ : this(env, new Arguments() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
+ {
+ }
+
  private BootstrapSampleTransform(IHost host, ModelLoadContext ctx, IDataView input)
  : base(host, input)
  {

src/Microsoft.ML.Transforms/CategoricalHashTransform.cs

@@ -86,6 +86,15 @@ public bool TryUnparse(StringBuilder sb)
  }
  }
 
+ private static class Defaults
+ {
+ public const int HashBits = 16;
+ public const uint Seed = 314489979;
+ public const bool Ordered = true;
+ public const int InvertHash = 0;
+ public const CategoricalTransform.OutputKind OutputKind = CategoricalTransform.OutputKind.Bag;
+ }
+
  /// <summary>
  /// This class is a merger of <see cref="HashTransform.Arguments"/> and <see cref="KeyToVectorTransform.Arguments"/>
  /// with join option removed
@@ -97,29 +106,61 @@ public sealed class Arguments : TransformInputBase
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Number of bits to hash into. Must be between 1 and 30, inclusive.",
  ShortName = "bits", SortOrder = 2)]
- public int HashBits = 16;
+ public int HashBits = Defaults.HashBits;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Hashing seed")]
- public uint Seed = 314489979;
+ public uint Seed = Defaults.Seed;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether the position of each term should be included in the hash", ShortName = "ord")]
- public bool Ordered = true;
+ public bool Ordered = Defaults.Ordered;
 
  [Argument(ArgumentType.AtMostOnce,
  HelpText = "Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit.",
  ShortName = "ih")]
- public int InvertHash;
+ public int InvertHash = Defaults.InvertHash;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Output kind: Bag (multi-set vector), Ind (indicator vector), or Key (index)",
  ShortName = "kind", SortOrder = 102)]
- public CategoricalTransform.OutputKind OutputKind = CategoricalTransform.OutputKind.Bag;
+ public CategoricalTransform.OutputKind OutputKind = Defaults.OutputKind;
  }
 
  internal const string Summary = "Converts the categorical value into an indicator array by hashing the value and using the hash as an index in the "
  + "bag. If the input column is a vector, a single indicator bag is returned for it.";
 
  public const string UserName = "Categorical Hash Transform";
 
+ /// <summary>
+ /// A helper method to create <see cref="CategoricalHashTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
+ /// <param name="hashBits">Number of bits to hash into. Must be between 1 and 30, inclusive.</param>
+ /// <param name="invertHash">Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit.</param>
+ /// <param name="outputKind">The type of output expected.</param>
+ public static IDataTransform Create(IHostEnvironment env, 
+ IDataView input, 
+ string name, 
+ string source =null, 
+ int hashBits = Defaults.HashBits, 
+ int invertHash = Defaults.InvertHash, 
+ CategoricalTransform.OutputKind outputKind = Defaults.OutputKind)
+ {
+ var args = new Arguments()
+ {
+ Column = new[] { new Column(){
+ Source = source ?? name,
+ Name = name
+ }
+ },
+ HashBits = hashBits,
+ InvertHash = invertHash,
+ OutputKind = outputKind
+ };
+ return Create(env, args, input);
+ }
+
  public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataView input)
  {
  Contracts.CheckValue(env, nameof(env));

src/Microsoft.ML.Transforms/CategoricalTransform.cs

@@ -38,15 +38,27 @@ public static class CategoricalTransform
  {
  public enum OutputKind : byte
  {
+ /// <summary>
+ /// Output is a bag (multi-set) vector
+ /// </summary>
  [TGUI(Label = "Output is a bag (multi-set) vector")]
  Bag = 1,
 
+ /// <summary>
+ /// Output is an indicator vector
+ /// </summary>
  [TGUI(Label = "Output is an indicator vector")]
  Ind = 2,
 
+ /// <summary>
+ /// Output is a key value
+ /// </summary>
  [TGUI(Label = "Output is a key value")]
  Key = 3,
 
+ /// <summary>
+ /// Output is binary encoded
+ /// </summary>
  [TGUI(Label = "Output is binary encoded")]
  Bin = 4,
  }
@@ -96,14 +108,19 @@ public bool TryUnparse(StringBuilder sb)
  }
  }
 
+ private static class Defaults
+ {
+ public const OutputKind OutKind = OutputKind.Ind;
+ }
+
  public sealed class Arguments : TermTransform.ArgumentsBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", ShortName = "col", SortOrder = 1)]
  public Column[] Column;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Output kind: Bag (multi-set vector), Ind (indicator vector), or Key (index)",
  ShortName = "kind", SortOrder = 102)]
- public OutputKind OutputKind = OutputKind.Ind;
+ public OutputKind OutputKind = Defaults.OutKind;
 
  public Arguments()
  {
@@ -118,6 +135,28 @@ public Arguments()
 
  public const string UserName = "Categorical Transform";
 
+ /// <summary>
+ /// A helper method to create <see cref="CategoricalTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
+ /// <param name="outputKind">The type of output expected.</param>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, string name, string source = null, OutputKind outputKind = Defaults.OutKind)
+ {
+ var args = new Arguments()
+ {
+ Column = new[] { new Column(){
+ Source = source ?? name,
+ Name = name
+ }
+ },
+ OutputKind = outputKind
+ };
+ return Create(env, args, input);
+ }
+
  public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataView input)
  {
  Contracts.CheckValue(env, nameof(env));

src/Microsoft.ML.Transforms/CountFeatureSelection.cs

@@ -28,17 +28,40 @@ public static class CountFeatureSelectionTransform
  public const string Summary = "Selects the slots for which the count of non-default values is greater than or equal to a threshold.";
  public const string UserName = "Count Feature Selection Transform";
 
+ private static class Defaults
+ {
+ public const long Count = 1;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Columns to use for feature selection", ShortName = "col", SortOrder = 1)]
  public string[] Column;
 
  [Argument(ArgumentType.Required, HelpText = "If the count of non-default values for a slot is greater than or equal to this threshold, the slot is preserved", ShortName = "c", SortOrder = 1)]
- public long Count = 1;
+ public long Count = Defaults.Count;
  }
 
  internal static string RegistrationName = "CountFeatureSelectionTransform";
 
+ /// <summary>
+ /// A helper method to create CountFeatureSelection transform for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="count">If the count of non-default values for a slot is greater than or equal to this threshold, the slot is preserved.</param>
+ /// <param name="columns">Columns to use for feature selection.</param>
+ /// <returns></returns>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, long count = Defaults.Count, params string[] columns)
+ {
+ var args = new Arguments()
+ {
+ Column = columns,
+ Count = count
+ };
+ return Create(env, args, input);
+ }
+
  /// <summary>
  /// Create method corresponding to SignatureDataTransform.
  /// </summary>

src/Microsoft.ML.Data/Transforms/ConcatTransform.cs

@@ -90,6 +90,19 @@ public bool TryUnparse(StringBuilder sb)
 
  public sealed class Arguments : TransformInputBase
  {
+ public Arguments()
+ {
+ }
+
+ public Arguments(string name, params string[] source)
+ {
+ Column = new[] { new Column()
+ {
+ Name = name,
+ Source = source
+ }};
+ }
+
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:srcs)", ShortName = "col", SortOrder = 1)]
  public Column[] Column;
  }
@@ -527,6 +540,18 @@ private static VersionInfo GetVersionInfo()
 
  public override ISchema Schema => _bindings;
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Input columns to concatenate.</param>
+ public ConcatTransform(IHostEnvironment env, IDataView input, string name, params string[] source)
+ : this(env, new Arguments(name, source), input)
+ {
+ }
+
  /// <summary>
  /// Public constructor corresponding to SignatureDataTransform.
  /// </summary>

src/Microsoft.ML.Data/Transforms/CopyColumnsTransform.cs

@@ -64,6 +64,18 @@ private static VersionInfo GetVersionInfo()
 
  private const string RegistrationName = "CopyColumns";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be copied.</param>
+ public CopyColumnsTransform(IHostEnvironment env, IDataView input, string name, string source)
+ : this(env, new Arguments(){ Column = new[] { new Column() { Source = source, Name = name }}}, input)
+ {
+ }
+
  public CopyColumnsTransform(IHostEnvironment env, Arguments args, IDataView input)
  : base(env, RegistrationName, env.CheckRef(args, nameof(args)).Column, input, null)
  {

src/Microsoft.ML.Data/Transforms/DropColumnsTransform.cs

@@ -237,6 +237,17 @@ private static VersionInfo GetVersionInfo()
  private const string DropRegistrationName = "DropColumns";
  private const string KeepRegistrationName = "KeepColumns";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="columnsToDrop">Name of the columns to be dropped.</param>
+ public DropColumnsTransform(IHostEnvironment env, IDataView input, params string[] columnsToDrop)
+ :this(env, new Arguments() { Column = columnsToDrop }, input)
+ {
+ }
+
  /// <summary>
  /// Public constructor corresponding to SignatureDataTransform.
  /// </summary>
@@ -383,4 +394,17 @@ public ValueGetter<TValue> GetGetter<TValue>(int col)
  }
  }
  }
+
+ public class KeepColumnsTransform
+ {
+ /// <summary>
+ /// A helper method to create <see cref="KeepColumnsTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="columnsToKeep">Name of the columns to be kept. All other columns will be removed.</param>
+ /// <returns></returns>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, params string[] columnsToKeep)
+ => new DropColumnsTransform(env, new DropColumnsTransform.KeepArguments() { Column = columnsToKeep }, input);
+ }
 }

src/Microsoft.ML.Data/Transforms/NAFilter.cs

@@ -28,13 +28,18 @@ namespace Microsoft.ML.Runtime.Data
 {
  public sealed class NAFilter : FilterBase
  {
+ private static class Defaults
+ {
+ public const bool Complement = false;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Column", ShortName = "col", SortOrder = 1)]
  public string[] Column;
 
  [Argument(ArgumentType.Multiple, HelpText = "If true, keep only rows that contain NA values, and filter the rest.")]
- public bool Complement;
+ public bool Complement = Defaults.Complement;
  }
 
  private sealed class ColInfo
@@ -72,6 +77,18 @@ private static VersionInfo GetVersionInfo()
  private readonly bool _complement;
  private const string RegistrationName = "MissingValueFilter";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="complement">If true, keep only rows that contain NA values, and filter the rest.</param>
+ /// <param name="columns">Name of the columns. Only these columns will be used to filter rows having 'NA' values.</param>
+ public NAFilter(IHostEnvironment env, IDataView input, bool complement = Defaults.Complement, params string[] columns)
+ : this(env, new Arguments() { Column = columns, Complement = complement }, input)
+ {
+ }
+
  public NAFilter(IHostEnvironment env, Arguments args, IDataView input)
  : base(env, RegistrationName, input)
  {

src/Microsoft.ML.Transforms/BootstrapSampleTransform.cs

@@ -25,20 +25,27 @@ namespace Microsoft.ML.Runtime.Data
  /// </summary>
  public sealed class BootstrapSampleTransform : FilterBase
  {
+ private static class Defaults
+ {
+ public const bool Complement = false;
+ public const bool ShuffleInput = true;
+ public const int PoolSize = 1000;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether this is the out-of-bag sample, that is, all those rows that are not selected by the transform.",
  ShortName = "comp")]
- public bool Complement;
+ public bool Complement = Defaults.Complement;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "The random seed. If unspecified random state will be instead derived from the environment.")]
  public uint? Seed;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.", ShortName = "si")]
- public bool ShuffleInput = true;
+ public bool ShuffleInput = Defaults.ShuffleInput;
 
  [Argument(ArgumentType.LastOccurenceWins, HelpText = "When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.", ShortName = "pool")]
- public int PoolSize = 1000;
+ public int PoolSize = Defaults.PoolSize;
  }
 
  internal const string Summary = "Approximate bootstrap sampling.";
@@ -76,6 +83,25 @@ public BootstrapSampleTransform(IHostEnvironment env, Arguments args, IDataView
  _poolSize = args.PoolSize;
  }
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="complement">Whether this is the out-of-bag sample, that is, all those rows that are not selected by the transform.</param>
+ /// <param name="seed">The random seed. If unspecified random state will be instead derived from the environment.</param>
+ /// <param name="shuffleInput">Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.</param>
+ /// <param name="poolSize">When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.</param>
+ public BootstrapSampleTransform(IHostEnvironment env, 
+ IDataView input, 
+ bool complement = Defaults.Complement, 
+ uint? seed = null, 
+ bool shuffleInput = Defaults.ShuffleInput, 
+ int poolSize = Defaults.PoolSize)
+ : this(env, new Arguments() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
+ {
+ }
+
  private BootstrapSampleTransform(IHost host, ModelLoadContext ctx, IDataView input)
  : base(host, input)
  {

src/Microsoft.ML.Transforms/CategoricalHashTransform.cs

@@ -86,6 +86,15 @@ public bool TryUnparse(StringBuilder sb)
  }
  }
 
+ private static class Defaults
+ {
+ public const int HashBits = 16;
+ public const uint Seed = 314489979;
+ public const bool Ordered = true;
+ public const int InvertHash = 0;
+ public const CategoricalTransform.OutputKind OutputKind = CategoricalTransform.OutputKind.Bag;
+ }
+
  /// <summary>
  /// This class is a merger of <see cref="HashTransform.Arguments"/> and <see cref="KeyToVectorTransform.Arguments"/>
  /// with join option removed
@@ -97,29 +106,61 @@ public sealed class Arguments : TransformInputBase
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Number of bits to hash into. Must be between 1 and 30, inclusive.",
  ShortName = "bits", SortOrder = 2)]
- public int HashBits = 16;
+ public int HashBits = Defaults.HashBits;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Hashing seed")]
- public uint Seed = 314489979;
+ public uint Seed = Defaults.Seed;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether the position of each term should be included in the hash", ShortName = "ord")]
- public bool Ordered = true;
+ public bool Ordered = Defaults.Ordered;
 
  [Argument(ArgumentType.AtMostOnce,
  HelpText = "Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit.",
  ShortName = "ih")]
- public int InvertHash;
+ public int InvertHash = Defaults.InvertHash;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Output kind: Bag (multi-set vector), Ind (indicator vector), or Key (index)",
  ShortName = "kind", SortOrder = 102)]
- public CategoricalTransform.OutputKind OutputKind = CategoricalTransform.OutputKind.Bag;
+ public CategoricalTransform.OutputKind OutputKind = Defaults.OutputKind;
  }
 
  internal const string Summary = "Converts the categorical value into an indicator array by hashing the value and using the hash as an index in the "
  + "bag. If the input column is a vector, a single indicator bag is returned for it.";
 
  public const string UserName = "Categorical Hash Transform";
 
+ /// <summary>
+ /// A helper method to create <see cref="CategoricalHashTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
+ /// <param name="hashBits">Number of bits to hash into. Must be between 1 and 30, inclusive.</param>
+ /// <param name="invertHash">Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit.</param>
+ /// <param name="outputKind">The type of output expected.</param>
+ public static IDataTransform Create(IHostEnvironment env, 
+ IDataView input, 
+ string name, 
+ string source =null, 
+ int hashBits = Defaults.HashBits, 
+ int invertHash = Defaults.InvertHash, 
+ CategoricalTransform.OutputKind outputKind = Defaults.OutputKind)
+ {
+ var args = new Arguments()
+ {
+ Column = new[] { new Column(){
+ Source = source ?? name,
+ Name = name
+ }
+ },
+ HashBits = hashBits,
+ InvertHash = invertHash,
+ OutputKind = outputKind
+ };
+ return Create(env, args, input);
+ }
+
  public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataView input)
  {
  Contracts.CheckValue(env, nameof(env));

src/Microsoft.ML.Transforms/CategoricalTransform.cs

@@ -38,15 +38,27 @@ public static class CategoricalTransform
  {
  public enum OutputKind : byte
  {
+ /// <summary>
+ /// Output is a bag (multi-set) vector
+ /// </summary>
  [TGUI(Label = "Output is a bag (multi-set) vector")]
  Bag = 1,
 
+ /// <summary>
+ /// Output is an indicator vector
+ /// </summary>
  [TGUI(Label = "Output is an indicator vector")]
  Ind = 2,
 
+ /// <summary>
+ /// Output is a key value
+ /// </summary>
  [TGUI(Label = "Output is a key value")]
  Key = 3,
 
+ /// <summary>
+ /// Output is binary encoded
+ /// </summary>
  [TGUI(Label = "Output is binary encoded")]
  Bin = 4,
  }
@@ -96,14 +108,19 @@ public bool TryUnparse(StringBuilder sb)
  }
  }
 
+ private static class Defaults
+ {
+ public const OutputKind OutKind = OutputKind.Ind;
+ }
+
  public sealed class Arguments : TermTransform.ArgumentsBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", ShortName = "col", SortOrder = 1)]
  public Column[] Column;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Output kind: Bag (multi-set vector), Ind (indicator vector), or Key (index)",
  ShortName = "kind", SortOrder = 102)]
- public OutputKind OutputKind = OutputKind.Ind;
+ public OutputKind OutputKind = Defaults.OutKind;
 
  public Arguments()
  {
@@ -118,6 +135,28 @@ public Arguments()
 
  public const string UserName = "Categorical Transform";
 
+ /// <summary>
+ /// A helper method to create <see cref="CategoricalTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
+ /// <param name="outputKind">The type of output expected.</param>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, string name, string source = null, OutputKind outputKind = Defaults.OutKind)
+ {
+ var args = new Arguments()
+ {
+ Column = new[] { new Column(){
+ Source = source ?? name,
+ Name = name
+ }
+ },
+ OutputKind = outputKind
+ };
+ return Create(env, args, input);
+ }
+
  public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataView input)
  {
  Contracts.CheckValue(env, nameof(env));

src/Microsoft.ML.Transforms/CountFeatureSelection.cs

@@ -28,17 +28,40 @@ public static class CountFeatureSelectionTransform
  public const string Summary = "Selects the slots for which the count of non-default values is greater than or equal to a threshold.";
  public const string UserName = "Count Feature Selection Transform";
 
+ private static class Defaults
+ {
+ public const long Count = 1;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Columns to use for feature selection", ShortName = "col", SortOrder = 1)]
  public string[] Column;
 
  [Argument(ArgumentType.Required, HelpText = "If the count of non-default values for a slot is greater than or equal to this threshold, the slot is preserved", ShortName = "c", SortOrder = 1)]
- public long Count = 1;
+ public long Count = Defaults.Count;
  }
 
  internal static string RegistrationName = "CountFeatureSelectionTransform";
 
+ /// <summary>
+ /// A helper method to create CountFeatureSelection transform for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="count">If the count of non-default values for a slot is greater than or equal to this threshold, the slot is preserved.</param>
+ /// <param name="columns">Columns to use for feature selection.</param>
+ /// <returns></returns>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, long count = Defaults.Count, params string[] columns)
+ {
+ var args = new Arguments()
+ {
+ Column = columns,
+ Count = count
+ };
+ return Create(env, args, input);
+ }
+
  /// <summary>
  /// Create method corresponding to SignatureDataTransform.
  /// </summary>

src/Microsoft.ML.Data/Transforms/ConcatTransform.cs

@@ -90,6 +90,19 @@ public bool TryUnparse(StringBuilder sb)
 
  public sealed class Arguments : TransformInputBase
  {
+ public Arguments()
+ {
+ }
+
+ public Arguments(string name, params string[] source)
+ {
+ Column = new[] { new Column()
+ {
+ Name = name,
+ Source = source
+ }};
+ }
+
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:srcs)", ShortName = "col", SortOrder = 1)]
  public Column[] Column;
  }
@@ -527,6 +540,18 @@ private static VersionInfo GetVersionInfo()
 
  public override ISchema Schema => _bindings;
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Input columns to concatenate.</param>
+ public ConcatTransform(IHostEnvironment env, IDataView input, string name, params string[] source)
+ : this(env, new Arguments(name, source), input)
+ {
+ }
+
  /// <summary>
  /// Public constructor corresponding to SignatureDataTransform.
  /// </summary>

src/Microsoft.ML.Data/Transforms/CopyColumnsTransform.cs

@@ -64,6 +64,18 @@ private static VersionInfo GetVersionInfo()
 
  private const string RegistrationName = "CopyColumns";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be copied.</param>
+ public CopyColumnsTransform(IHostEnvironment env, IDataView input, string name, string source)
+ : this(env, new Arguments(){ Column = new[] { new Column() { Source = source, Name = name }}}, input)
+ {
+ }
+
  public CopyColumnsTransform(IHostEnvironment env, Arguments args, IDataView input)
  : base(env, RegistrationName, env.CheckRef(args, nameof(args)).Column, input, null)
  {

src/Microsoft.ML.Data/Transforms/DropColumnsTransform.cs

@@ -237,6 +237,17 @@ private static VersionInfo GetVersionInfo()
  private const string DropRegistrationName = "DropColumns";
  private const string KeepRegistrationName = "KeepColumns";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="columnsToDrop">Name of the columns to be dropped.</param>
+ public DropColumnsTransform(IHostEnvironment env, IDataView input, params string[] columnsToDrop)
+ :this(env, new Arguments() { Column = columnsToDrop }, input)
+ {
+ }
+
  /// <summary>
  /// Public constructor corresponding to SignatureDataTransform.
  /// </summary>
@@ -383,4 +394,17 @@ public ValueGetter<TValue> GetGetter<TValue>(int col)
  }
  }
  }
+
+ public class KeepColumnsTransform
+ {
+ /// <summary>
+ /// A helper method to create <see cref="KeepColumnsTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="columnsToKeep">Name of the columns to be kept. All other columns will be removed.</param>
+ /// <returns></returns>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, params string[] columnsToKeep)
+ => new DropColumnsTransform(env, new DropColumnsTransform.KeepArguments() { Column = columnsToKeep }, input);
+ }
 }

src/Microsoft.ML.Data/Transforms/NAFilter.cs

@@ -28,13 +28,18 @@ namespace Microsoft.ML.Runtime.Data
 {
  public sealed class NAFilter : FilterBase
  {
+ private static class Defaults
+ {
+ public const bool Complement = false;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Column", ShortName = "col", SortOrder = 1)]
  public string[] Column;
 
  [Argument(ArgumentType.Multiple, HelpText = "If true, keep only rows that contain NA values, and filter the rest.")]
- public bool Complement;
+ public bool Complement = Defaults.Complement;
  }
 
  private sealed class ColInfo
@@ -72,6 +77,18 @@ private static VersionInfo GetVersionInfo()
  private readonly bool _complement;
  private const string RegistrationName = "MissingValueFilter";
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="complement">If true, keep only rows that contain NA values, and filter the rest.</param>
+ /// <param name="columns">Name of the columns. Only these columns will be used to filter rows having 'NA' values.</param>
+ public NAFilter(IHostEnvironment env, IDataView input, bool complement = Defaults.Complement, params string[] columns)
+ : this(env, new Arguments() { Column = columns, Complement = complement }, input)
+ {
+ }
+
  public NAFilter(IHostEnvironment env, Arguments args, IDataView input)
  : base(env, RegistrationName, input)
  {

src/Microsoft.ML.Transforms/BootstrapSampleTransform.cs

@@ -25,20 +25,27 @@ namespace Microsoft.ML.Runtime.Data
  /// </summary>
  public sealed class BootstrapSampleTransform : FilterBase
  {
+ private static class Defaults
+ {
+ public const bool Complement = false;
+ public const bool ShuffleInput = true;
+ public const int PoolSize = 1000;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether this is the out-of-bag sample, that is, all those rows that are not selected by the transform.",
  ShortName = "comp")]
- public bool Complement;
+ public bool Complement = Defaults.Complement;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "The random seed. If unspecified random state will be instead derived from the environment.")]
  public uint? Seed;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.", ShortName = "si")]
- public bool ShuffleInput = true;
+ public bool ShuffleInput = Defaults.ShuffleInput;
 
  [Argument(ArgumentType.LastOccurenceWins, HelpText = "When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.", ShortName = "pool")]
- public int PoolSize = 1000;
+ public int PoolSize = Defaults.PoolSize;
  }
 
  internal const string Summary = "Approximate bootstrap sampling.";
@@ -76,6 +83,25 @@ public BootstrapSampleTransform(IHostEnvironment env, Arguments args, IDataView
  _poolSize = args.PoolSize;
  }
 
+ /// <summary>
+ /// Convenience constructor for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="complement">Whether this is the out-of-bag sample, that is, all those rows that are not selected by the transform.</param>
+ /// <param name="seed">The random seed. If unspecified random state will be instead derived from the environment.</param>
+ /// <param name="shuffleInput">Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.</param>
+ /// <param name="poolSize">When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.</param>
+ public BootstrapSampleTransform(IHostEnvironment env, 
+ IDataView input, 
+ bool complement = Defaults.Complement, 
+ uint? seed = null, 
+ bool shuffleInput = Defaults.ShuffleInput, 
+ int poolSize = Defaults.PoolSize)
+ : this(env, new Arguments() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
+ {
+ }
+
  private BootstrapSampleTransform(IHost host, ModelLoadContext ctx, IDataView input)
  : base(host, input)
  {

src/Microsoft.ML.Transforms/CategoricalHashTransform.cs

@@ -86,6 +86,15 @@ public bool TryUnparse(StringBuilder sb)
  }
  }
 
+ private static class Defaults
+ {
+ public const int HashBits = 16;
+ public const uint Seed = 314489979;
+ public const bool Ordered = true;
+ public const int InvertHash = 0;
+ public const CategoricalTransform.OutputKind OutputKind = CategoricalTransform.OutputKind.Bag;
+ }
+
  /// <summary>
  /// This class is a merger of <see cref="HashTransform.Arguments"/> and <see cref="KeyToVectorTransform.Arguments"/>
  /// with join option removed
@@ -97,29 +106,61 @@ public sealed class Arguments : TransformInputBase
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Number of bits to hash into. Must be between 1 and 30, inclusive.",
  ShortName = "bits", SortOrder = 2)]
- public int HashBits = 16;
+ public int HashBits = Defaults.HashBits;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Hashing seed")]
- public uint Seed = 314489979;
+ public uint Seed = Defaults.Seed;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Whether the position of each term should be included in the hash", ShortName = "ord")]
- public bool Ordered = true;
+ public bool Ordered = Defaults.Ordered;
 
  [Argument(ArgumentType.AtMostOnce,
  HelpText = "Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit.",
  ShortName = "ih")]
- public int InvertHash;
+ public int InvertHash = Defaults.InvertHash;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Output kind: Bag (multi-set vector), Ind (indicator vector), or Key (index)",
  ShortName = "kind", SortOrder = 102)]
- public CategoricalTransform.OutputKind OutputKind = CategoricalTransform.OutputKind.Bag;
+ public CategoricalTransform.OutputKind OutputKind = Defaults.OutputKind;
  }
 
  internal const string Summary = "Converts the categorical value into an indicator array by hashing the value and using the hash as an index in the "
  + "bag. If the input column is a vector, a single indicator bag is returned for it.";
 
  public const string UserName = "Categorical Hash Transform";
 
+ /// <summary>
+ /// A helper method to create <see cref="CategoricalHashTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
+ /// <param name="hashBits">Number of bits to hash into. Must be between 1 and 30, inclusive.</param>
+ /// <param name="invertHash">Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit.</param>
+ /// <param name="outputKind">The type of output expected.</param>
+ public static IDataTransform Create(IHostEnvironment env, 
+ IDataView input, 
+ string name, 
+ string source =null, 
+ int hashBits = Defaults.HashBits, 
+ int invertHash = Defaults.InvertHash, 
+ CategoricalTransform.OutputKind outputKind = Defaults.OutputKind)
+ {
+ var args = new Arguments()
+ {
+ Column = new[] { new Column(){
+ Source = source ?? name,
+ Name = name
+ }
+ },
+ HashBits = hashBits,
+ InvertHash = invertHash,
+ OutputKind = outputKind
+ };
+ return Create(env, args, input);
+ }
+
  public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataView input)
  {
  Contracts.CheckValue(env, nameof(env));

src/Microsoft.ML.Transforms/CategoricalTransform.cs

@@ -38,15 +38,27 @@ public static class CategoricalTransform
  {
  public enum OutputKind : byte
  {
+ /// <summary>
+ /// Output is a bag (multi-set) vector
+ /// </summary>
  [TGUI(Label = "Output is a bag (multi-set) vector")]
  Bag = 1,
 
+ /// <summary>
+ /// Output is an indicator vector
+ /// </summary>
  [TGUI(Label = "Output is an indicator vector")]
  Ind = 2,
 
+ /// <summary>
+ /// Output is a key value
+ /// </summary>
  [TGUI(Label = "Output is a key value")]
  Key = 3,
 
+ /// <summary>
+ /// Output is binary encoded
+ /// </summary>
  [TGUI(Label = "Output is binary encoded")]
  Bin = 4,
  }
@@ -96,14 +108,19 @@ public bool TryUnparse(StringBuilder sb)
  }
  }
 
+ private static class Defaults
+ {
+ public const OutputKind OutKind = OutputKind.Ind;
+ }
+
  public sealed class Arguments : TermTransform.ArgumentsBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", ShortName = "col", SortOrder = 1)]
  public Column[] Column;
 
  [Argument(ArgumentType.AtMostOnce, HelpText = "Output kind: Bag (multi-set vector), Ind (indicator vector), or Key (index)",
  ShortName = "kind", SortOrder = 102)]
- public OutputKind OutputKind = OutputKind.Ind;
+ public OutputKind OutputKind = Defaults.OutKind;
 
  public Arguments()
  {
@@ -118,6 +135,28 @@ public Arguments()
 
  public const string UserName = "Categorical Transform";
 
+ /// <summary>
+ /// A helper method to create <see cref="CategoricalTransform"/> for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="name">Name of the output column.</param>
+ /// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
+ /// <param name="outputKind">The type of output expected.</param>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, string name, string source = null, OutputKind outputKind = Defaults.OutKind)
+ {
+ var args = new Arguments()
+ {
+ Column = new[] { new Column(){
+ Source = source ?? name,
+ Name = name
+ }
+ },
+ OutputKind = outputKind
+ };
+ return Create(env, args, input);
+ }
+
  public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataView input)
  {
  Contracts.CheckValue(env, nameof(env));

src/Microsoft.ML.Transforms/CountFeatureSelection.cs

@@ -28,17 +28,40 @@ public static class CountFeatureSelectionTransform
  public const string Summary = "Selects the slots for which the count of non-default values is greater than or equal to a threshold.";
  public const string UserName = "Count Feature Selection Transform";
 
+ private static class Defaults
+ {
+ public const long Count = 1;
+ }
+
  public sealed class Arguments : TransformInputBase
  {
  [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Columns to use for feature selection", ShortName = "col", SortOrder = 1)]
  public string[] Column;
 
  [Argument(ArgumentType.Required, HelpText = "If the count of non-default values for a slot is greater than or equal to this threshold, the slot is preserved", ShortName = "c", SortOrder = 1)]
- public long Count = 1;
+ public long Count = Defaults.Count;
  }
 
  internal static string RegistrationName = "CountFeatureSelectionTransform";
 
+ /// <summary>
+ /// A helper method to create CountFeatureSelection transform for public facing API.
+ /// </summary>
+ /// <param name="env">Host Environment.</param>
+ /// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
+ /// <param name="count">If the count of non-default values for a slot is greater than or equal to this threshold, the slot is preserved.</param>
+ /// <param name="columns">Columns to use for feature selection.</param>
+ /// <returns></returns>
+ public static IDataTransform Create(IHostEnvironment env, IDataView input, long count = Defaults.Count, params string[] columns)
+ {
+ var args = new Arguments()
+ {
+ Column = columns,
+ Count = count
+ };
+ return Create(env, args, input);
+ }
+
  /// <summary>
  /// Create method corresponding to SignatureDataTransform.
  /// </summary>