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Random doc updates #7476

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doc updates
gewarren Jun 5, 2025
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gewarren Jun 5, 2025
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Update src/Microsoft.ML.Transforms/CustomMappingTransformer.cs
gewarren Jun 10, 2025
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2 changes: 1 addition & 1 deletion src/Microsoft.ML.Transforms/CategoricalCatalog.cs
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Expand Up @@ -51,7 +51,7 @@ public static OneHotEncodingEstimator OneHotEncoding(this TransformsCatalog.Cate
new[] { new OneHotEncodingEstimator.ColumnOptions(outputColumnName, inputColumnName, outputKind, maximumNumberOfKeys, keyOrdinality) }, keyData);

/// <summary>
/// Create a <see cref="OneHotEncodingEstimator"/>, which converts one or more input text columns specified in <paramref name="columns"/>
/// Creates a <see cref="OneHotEncodingEstimator"/>, which converts one or more input text columns specified in <paramref name="columns"/>
/// into as many columns of one-hot encoded vectors.
/// </summary>
/// <remarks>If multiple columns are passed to the estimator, all of the columns will be processed in a single pass over the data.
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16 changes: 8 additions & 8 deletions src/Microsoft.ML.Transforms/CustomMappingTransformer.cs
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Expand Up @@ -33,14 +33,14 @@ public sealed class CustomMappingTransformer<TSrc, TDst> : ITransformer
/// </summary>
bool ITransformer.IsRowToRowMapper => true;

/// <summary>
/// Create a custom mapping of input columns to output columns.
/// </summary>
/// <param name="env">The host environment</param>
/// <param name="mapAction">The action by which we map source to destination columns</param>
/// <param name="contractName">The name of the action (will be saved to the model).</param>
/// <param name="inputSchemaDefinition">Additional parameters for schema mapping between <typeparamref name="TSrc"/> and input data.</param>
/// <param name="outputSchemaDefinition">Additional parameters for schema mapping between <typeparamref name="TDst"/> and output data.</param>
/// <summary>
/// Creates a custom mapping of input columns to output columns.
/// </summary>
/// <param name="env">The host environment that provides services and logging capabilities.</param>
/// <param name="mapAction">The action that maps source columns to destination columns.</param>
/// <param name="contractName">The name of the action that will be saved to the model.</param>
/// <param name="inputSchemaDefinition">Additional parameters for schema mapping between <typeparamref name="TSrc"/> and input data.</param>
/// <param name="outputSchemaDefinition">Additional parameters for schema mapping between <typeparamref name="TDst"/> and output data.</param>
internal CustomMappingTransformer(IHostEnvironment env, Action<TSrc, TDst> mapAction, string contractName,
SchemaDefinition inputSchemaDefinition = null, SchemaDefinition outputSchemaDefinition = null)
{
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46 changes: 27 additions & 19 deletions src/Microsoft.ML.Transforms/Text/TextFeaturizingEstimator.cs
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Expand Up @@ -32,8 +32,8 @@ namespace Microsoft.ML.Transforms.Text
public interface IStopWordsRemoverOptions { }

/// <summary>
/// An estimator that turns a collection of text documents into numerical feature vectors.
/// The feature vectors are normalized counts of word and/or character n-grams (based on the options supplied).
/// Represents an estimator that turns a collection of text documents into numerical feature vectors.
/// The feature vectors are normalized counts of word or character n-grams (based on the options supplied).
/// </summary>
/// <remarks>
/// <format type="text/markdown"><![CDATA[
Expand All @@ -51,23 +51,23 @@ public interface IStopWordsRemoverOptions { }
/// * [Tokenization](https://en.wikipedia.org/wiki/Lexical_analysis#Tokenization)
/// * [Text normalization](https://en.wikipedia.org/wiki/Text_normalization)
/// * [Predefined and custom stopwords removal](https://en.wikipedia.org/wiki/Stop_words)
/// * [Word-based or character-based Ngram extraction and SkipGram extraction (through the advanced [options](xref:Microsoft.ML.Transforms.TextFeaturizingEstimator.Options.WordFeatureExtractor))](https://en.wikipedia.org/wiki/N-gram)
/// * [Word-based or character-based Ngram extraction and SkipGram extraction](https://en.wikipedia.org/wiki/N-gram)
/// * [TF, IDF or TF-IDF](https://en.wikipedia.org/wiki/Tf%E2%80%93idf)
/// * [L-p vector normalization](xref: Microsoft.ML.Transforms.LpNormNormalizingTransformer)
///
/// By default the features are made of (word/character) n-grams/skip-grams​ and the number of features are equal to the vocabulary size found by analyzing the data.
/// By default the features are made of (word/character) n-grams/skip-grams, and the number of features is equal to the vocabulary size found by analyzing the data.
/// To output an additional column with the tokens generated, use [OutputTokensColumnName](xref:Microsoft.ML.Transforms.Text.TextFeaturizingEstimator.Options.OutputTokensColumnName).
/// The number of features can also be specified by selecting the maximum number of n-gram to keep in the <xref:Microsoft.ML.Transforms.Text.TextFeaturizingEstimator.Options>, where the estimator can be further tuned.
///
/// Check the See Also section for links to usage examples.
/// For links to usage examples, see <see cref="TextCatalog.FeaturizeText(TransformsCatalog.TextTransforms, string, Options, string[])"/> and <see cref="TextCatalog.FeaturizeText(TransformsCatalog.TextTransforms, string, string)"/>.
/// ]]></format>
/// </remarks>
/// <seealso cref="TextCatalog.FeaturizeText(TransformsCatalog.TextTransforms, string, Options, string[])"/>
/// <seealso cref="TextCatalog.FeaturizeText(TransformsCatalog.TextTransforms, string, string)"/>
public sealed class TextFeaturizingEstimator : IEstimator<ITransformer>
{
/// <summary>
/// Text language. This enumeration is serialized.
/// Specifies text languages. This enumeration is serialized.
/// </summary>
public enum Language
{
Expand All @@ -81,7 +81,7 @@ public enum Language
}

/// <summary>
/// Text vector normalizer kind.
/// Specifies the kinds of text vector normalizers.
/// </summary>
public enum NormFunction
{
Expand Down Expand Up @@ -121,7 +121,7 @@ internal bool TryUnparse(StringBuilder sb)
}

/// <summary>
/// Advanced options for the <see cref="TextFeaturizingEstimator"/>.
/// Provides advanced options for the <see cref="TextFeaturizingEstimator"/>.
/// </summary>
public sealed class Options : TransformInputBase
{
Expand All @@ -140,18 +140,20 @@ public sealed class Options : TransformInputBase
private IStopWordsRemoverOptions _stopWordsRemoverOptions;

/// <summary>
/// Option to set type of stop word remover to use.
/// Gets or sets the type of stop word remover to use.
/// </summary>
/// <remarks>
/// The following options are available
/// <list type="bullet">
/// <item>
/// <description>The <see cref="StopWordsRemovingEstimator.Options"/> removes the language specific list of stop words from the input.</description>
/// <description>The <see cref="StopWordsRemovingEstimator.Options"/> removes the language-specific list of stop words from the input.</description>
/// </item>
/// <item>
/// <description>The <see cref="CustomStopWordsRemovingEstimator.Options"/> uses user provided list of stop words.</description>
/// <description>The <see cref="CustomStopWordsRemovingEstimator.Options"/> uses a user-provided list of stop words.</description>
/// </item>
/// </list>
/// Setting this to 'null' does not remove stop words from the input.
/// </summary>
/// </remarks>
public IStopWordsRemoverOptions StopWordsRemoverOptions
{
get { return _stopWordsRemoverOptions; }
Expand Down Expand Up @@ -208,15 +210,17 @@ public IStopWordsRemoverOptions StopWordsRemoverOptions
private WordBagEstimator.Options _wordFeatureExtractor;

/// <summary>
/// Norm of the output vector. It will be normalized to one.
/// Gets the norm of the output vector. It will be normalized to one.
/// </summary>
[Argument(ArgumentType.AtMostOnce, HelpText = "Normalize vectors (rows) individually by rescaling them to unit norm.", Name = "VectorNormalizer", ShortName = "norm", SortOrder = 13)]
public NormFunction Norm = NormFunction.L2;

/// <summary>
/// Ngram feature extractor to use for words (WordBag/WordHashBag).
/// Set to <see langword="null" /> to turn off n-gram generation for words.
/// Gets or sets the n-gram feature extractor to use for words (WordBag/WordHashBag).
/// </summary>
/// <value>
/// Set to <see langword="null" /> to turn off n-gram generation for words.
/// </value>
public WordBagEstimator.Options WordFeatureExtractor
{
get { return _wordFeatureExtractor; }
Expand Down Expand Up @@ -247,9 +251,11 @@ public WordBagEstimator.Options WordFeatureExtractor
private WordBagEstimator.Options _charFeatureExtractor;

/// <summary>
/// Ngram feature extractor to use for characters (WordBag/WordHashBag).
/// Set to <see langword="null" /> to turn off n-gram generation for characters.
/// Gets or sets the n-gram feature extractor to use for characters (WordBag/WordHashBag).
/// </summary>
/// <value>
/// Set to <see langword="null" /> to turn off n-gram generation for characters.
/// </value>
public WordBagEstimator.Options CharFeatureExtractor
{
get { return _charFeatureExtractor; }
Expand Down Expand Up @@ -625,9 +631,11 @@ private static string GenerateColumnName(DataViewSchema schema, string srcName,
}

/// <summary>
/// Returns the <see cref="SchemaShape"/> of the schema which will be produced by the transformer.
/// Used for schema propagation and verification in a pipeline.
/// Returns the <see cref="SchemaShape"/> of the schema that will be produced by the transformer.
/// </summary>
/// <remarks>
/// This method is used for schema propagation and verification in a pipeline.
/// </remarks>
public SchemaShape GetOutputSchema(SchemaShape inputSchema)
{
_host.CheckValue(inputSchema, nameof(inputSchema));
Expand Down
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