CategoricalCatalog.xml

<Type Name="CategoricalCatalog" FullName="Microsoft.ML.CategoricalCatalog">
  <TypeSignature Language="C#" Value="public static class CategoricalCatalog" />
  <TypeSignature Language="ILAsm" Value=".class public auto ansi abstract sealed beforefieldinit CategoricalCatalog extends System.Object" />
  <TypeSignature Language="DocId" Value="T:Microsoft.ML.CategoricalCatalog" />
  <TypeSignature Language="VB.NET" Value="Public Module CategoricalCatalog" />
  <TypeSignature Language="F#" Value="type CategoricalCatalog = class" />
  <AssemblyInfo>
    <AssemblyName>Microsoft.ML.Transforms</AssemblyName>
    <AssemblyVersion>1.0.0.0</AssemblyVersion>
  </AssemblyInfo>
  <Base>
    <BaseTypeName>System.Object</BaseTypeName>
  </Base>
  <Interfaces />
  <Docs>
    <summary>
            Collection of extension methods for <see cref="T:Microsoft.ML.TransformsCatalog.CategoricalTransforms" /> to create categorical
            transformer components.
            </summary>
    <remarks>To be added.</remarks>
  </Docs>
  <Members>
    <Member MemberName="OneHotEncoding">
      <MemberSignature Language="C#" Value="public static Microsoft.ML.Transforms.OneHotEncodingEstimator OneHotEncoding (this Microsoft.ML.TransformsCatalog.CategoricalTransforms catalog, Microsoft.ML.InputOutputColumnPair[] columns, Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind outputKind = Microsoft.ML.Transforms.OneHotEncodingEstimator+OutputKind.Indicator, int maximumNumberOfKeys = 1000000, Microsoft.ML.Transforms.ValueToKeyMappingEstimator.KeyOrdinality keyOrdinality = Microsoft.ML.Transforms.ValueToKeyMappingEstimator+KeyOrdinality.ByOccurrence, Microsoft.ML.IDataView keyData = default);" />
      <MemberSignature Language="ILAsm" Value=".method public static hidebysig class Microsoft.ML.Transforms.OneHotEncodingEstimator OneHotEncoding(class Microsoft.ML.TransformsCatalog/CategoricalTransforms catalog, class Microsoft.ML.InputOutputColumnPair[] columns, valuetype Microsoft.ML.Transforms.OneHotEncodingEstimator/OutputKind outputKind, int32 maximumNumberOfKeys, valuetype Microsoft.ML.Transforms.ValueToKeyMappingEstimator/KeyOrdinality keyOrdinality, class Microsoft.ML.IDataView keyData) cil managed" />
      <MemberSignature Language="DocId" Value="M:Microsoft.ML.CategoricalCatalog.OneHotEncoding(Microsoft.ML.TransformsCatalog.CategoricalTransforms,Microsoft.ML.InputOutputColumnPair[],Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind,System.Int32,Microsoft.ML.Transforms.ValueToKeyMappingEstimator.KeyOrdinality,Microsoft.ML.IDataView)" />
      <MemberSignature Language="VB.NET" Value="&lt;Extension()&gt;&#xA;Public Function OneHotEncoding (catalog As TransformsCatalog.CategoricalTransforms, columns As InputOutputColumnPair(), Optional outputKind As OneHotEncodingEstimator.OutputKind = Microsoft.ML.Transforms.OneHotEncodingEstimator+OutputKind.Indicator, Optional maximumNumberOfKeys As Integer = 1000000, Optional keyOrdinality As ValueToKeyMappingEstimator.KeyOrdinality = Microsoft.ML.Transforms.ValueToKeyMappingEstimator+KeyOrdinality.ByOccurrence, Optional keyData As IDataView = Nothing) As OneHotEncodingEstimator" />
      <MemberSignature Language="F#" Value="static member OneHotEncoding : Microsoft.ML.TransformsCatalog.CategoricalTransforms * Microsoft.ML.InputOutputColumnPair[] * Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind * int * Microsoft.ML.Transforms.ValueToKeyMappingEstimator.KeyOrdinality * Microsoft.ML.IDataView -&gt; Microsoft.ML.Transforms.OneHotEncodingEstimator" Usage="Microsoft.ML.CategoricalCatalog.OneHotEncoding (catalog, columns, outputKind, maximumNumberOfKeys, keyOrdinality, keyData)" />
      <MemberType>Method</MemberType>
      <AssemblyInfo>
        <AssemblyName>Microsoft.ML.Transforms</AssemblyName>
        <AssemblyVersion>1.0.0.0</AssemblyVersion>
      </AssemblyInfo>
      <ReturnValue>
        <ReturnType>Microsoft.ML.Transforms.OneHotEncodingEstimator</ReturnType>
      </ReturnValue>
      <Parameters>
        <Parameter Name="catalog" Type="Microsoft.ML.TransformsCatalog+CategoricalTransforms" RefType="this" />
        <Parameter Name="columns" Type="Microsoft.ML.InputOutputColumnPair[]" />
        <Parameter Name="outputKind" Type="Microsoft.ML.Transforms.OneHotEncodingEstimator+OutputKind" />
        <Parameter Name="maximumNumberOfKeys" Type="System.Int32" />
        <Parameter Name="keyOrdinality" Type="Microsoft.ML.Transforms.ValueToKeyMappingEstimator+KeyOrdinality" />
        <Parameter Name="keyData" Type="Microsoft.ML.IDataView" />
      </Parameters>
      <Docs>
        <param name="catalog">The transform catalog.</param>
        <param name="columns">The pairs of input and output columns. The output columns' data type will be a vector of <see cref="T:System.Single" /> if <paramref name="outputKind" /> is
            <see cref="F:Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind.Bag" />, <see cref="F:Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind.Indicator" />, and <see cref="F:Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind.Binary" />.
            If <paramref name="outputKind" /> is <see cref="F:Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind.Key" />, the output columns' data type will be a key in the case of scalar input column
            or a vector of keys in the case of a vector input column.</param>
        <param name="outputKind">Output kind: Bag (multi-set vector), Ind (indicator vector), Key (index), or Binary encoded indicator vector.</param>
        <param name="maximumNumberOfKeys">Maximum number of terms to keep per column when auto-training.</param>
        <param name="keyOrdinality">How items should be ordered when vectorized. If <see cref="F:Microsoft.ML.Transforms.ValueToKeyMappingEstimator.KeyOrdinality.ByOccurrence" />
            choosen they will be in the order encountered. If <see cref="F:Microsoft.ML.Transforms.ValueToKeyMappingEstimator.KeyOrdinality.ByValue" />,
            items are sorted according to their default comparison, for example, text sorting will be case sensitive (for example, 'A' then 'Z' then 'a').</param>
        <param name="keyData">Specifies an ordering for the encoding. If specified, this should be a single column data view,
            and the key-values will be taken from that column. If unspecified, the ordering will be determined from the input data upon fitting.</param>
        <summary>
            Create a <see cref="T:Microsoft.ML.Transforms.OneHotEncodingEstimator" />, which converts one or more input text columns specified in <paramref name="columns" />
            into as many columns of one-hot encoded vectors.
            </summary>
        <returns>To be added.</returns>
        <remarks>If multiple columns are passed to the estimator, all of the columns will be processed in a single pass over the data.
            Therefore, it is more efficient to specify one estimator with many columns than it is to specify many estimators each with a single column.</remarks>
        <example>
          <format type="text/markdown"><![CDATA[
             [!code-csharp[OneHotEncoding](~/../docs/samples/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Categorical/OneHotEncodingMultiColumn.cs)]
            ]]></format>
        </example>
      </Docs>
    </Member>
    <Member MemberName="OneHotEncoding">
      <MemberSignature Language="C#" Value="public static Microsoft.ML.Transforms.OneHotEncodingEstimator OneHotEncoding (this Microsoft.ML.TransformsCatalog.CategoricalTransforms catalog, string outputColumnName, string inputColumnName = default, Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind outputKind = Microsoft.ML.Transforms.OneHotEncodingEstimator+OutputKind.Indicator, int maximumNumberOfKeys = 1000000, Microsoft.ML.Transforms.ValueToKeyMappingEstimator.KeyOrdinality keyOrdinality = Microsoft.ML.Transforms.ValueToKeyMappingEstimator+KeyOrdinality.ByOccurrence, Microsoft.ML.IDataView keyData = default);" />
      <MemberSignature Language="ILAsm" Value=".method public static hidebysig class Microsoft.ML.Transforms.OneHotEncodingEstimator OneHotEncoding(class Microsoft.ML.TransformsCatalog/CategoricalTransforms catalog, string outputColumnName, string inputColumnName, valuetype Microsoft.ML.Transforms.OneHotEncodingEstimator/OutputKind outputKind, int32 maximumNumberOfKeys, valuetype Microsoft.ML.Transforms.ValueToKeyMappingEstimator/KeyOrdinality keyOrdinality, class Microsoft.ML.IDataView keyData) cil managed" />
      <MemberSignature Language="DocId" Value="M:Microsoft.ML.CategoricalCatalog.OneHotEncoding(Microsoft.ML.TransformsCatalog.CategoricalTransforms,System.String,System.String,Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind,System.Int32,Microsoft.ML.Transforms.ValueToKeyMappingEstimator.KeyOrdinality,Microsoft.ML.IDataView)" />
      <MemberSignature Language="VB.NET" Value="&lt;Extension()&gt;&#xA;Public Function OneHotEncoding (catalog As TransformsCatalog.CategoricalTransforms, outputColumnName As String, Optional inputColumnName As String = Nothing, Optional outputKind As OneHotEncodingEstimator.OutputKind = Microsoft.ML.Transforms.OneHotEncodingEstimator+OutputKind.Indicator, Optional maximumNumberOfKeys As Integer = 1000000, Optional keyOrdinality As ValueToKeyMappingEstimator.KeyOrdinality = Microsoft.ML.Transforms.ValueToKeyMappingEstimator+KeyOrdinality.ByOccurrence, Optional keyData As IDataView = Nothing) As OneHotEncodingEstimator" />
      <MemberSignature Language="F#" Value="static member OneHotEncoding : Microsoft.ML.TransformsCatalog.CategoricalTransforms * string * string * Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind * int * Microsoft.ML.Transforms.ValueToKeyMappingEstimator.KeyOrdinality * Microsoft.ML.IDataView -&gt; Microsoft.ML.Transforms.OneHotEncodingEstimator" Usage="Microsoft.ML.CategoricalCatalog.OneHotEncoding (catalog, outputColumnName, inputColumnName, outputKind, maximumNumberOfKeys, keyOrdinality, keyData)" />
      <MemberType>Method</MemberType>
      <AssemblyInfo>
        <AssemblyName>Microsoft.ML.Transforms</AssemblyName>
        <AssemblyVersion>1.0.0.0</AssemblyVersion>
      </AssemblyInfo>
      <ReturnValue>
        <ReturnType>Microsoft.ML.Transforms.OneHotEncodingEstimator</ReturnType>
      </ReturnValue>
      <Parameters>
        <Parameter Name="catalog" Type="Microsoft.ML.TransformsCatalog+CategoricalTransforms" RefType="this" />
        <Parameter Name="outputColumnName" Type="System.String" />
        <Parameter Name="inputColumnName" Type="System.String" />
        <Parameter Name="outputKind" Type="Microsoft.ML.Transforms.OneHotEncodingEstimator+OutputKind" />
        <Parameter Name="maximumNumberOfKeys" Type="System.Int32" />
        <Parameter Name="keyOrdinality" Type="Microsoft.ML.Transforms.ValueToKeyMappingEstimator+KeyOrdinality" />
        <Parameter Name="keyData" Type="Microsoft.ML.IDataView" />
      </Parameters>
      <Docs>
        <param name="catalog">The transform catalog.</param>
        <param name="outputColumnName">Name of the column resulting from the transformation of <paramref name="inputColumnName" />.
            This column's data type will be a vector of <see cref="T:System.Single" /> if <paramref name="outputKind" /> is
            <see cref="F:Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind.Bag" />, <see cref="F:Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind.Indicator" />, and <see cref="F:Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind.Binary" />.
            If <paramref name="outputKind" /> is <see cref="F:Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind.Key" />, this column's data type will be a key in the case of a scalar input column
            or a vector of keys in the case of a vector input column.</param>
        <param name="inputColumnName">Name of column to convert to one-hot vectors. If set to <see langword="null" />, the value of the <paramref name="outputColumnName" />
            will be used as source. This column's data type can be scalar or vector of numeric, text, boolean, <see cref="T:System.DateTime" /> or <see cref="T:System.DateTimeOffset" />,</param>
        <param name="outputKind">Output kind: Bag (multi-set vector), Indicator (indicator vector), Key (index), or Binary encoded indicator vector.</param>
        <param name="maximumNumberOfKeys">Maximum number of terms to keep per column when auto-training.</param>
        <param name="keyOrdinality">How items should be ordered when vectorized. If <see cref="F:Microsoft.ML.Transforms.ValueToKeyMappingEstimator.KeyOrdinality.ByOccurrence" />
            choosen they will be in the order encountered. If <see cref="F:Microsoft.ML.Transforms.ValueToKeyMappingEstimator.KeyOrdinality.ByValue" />,
            items are sorted according to their default comparison, for example, text sorting will be case sensitive (for example, 'A' then 'Z' then 'a').</param>
        <param name="keyData">Specifies an ordering for the encoding. If specified, this should be a single column data view,
            and the key-values will be taken from that column. If unspecified, the ordering will be determined from the input data upon fitting.</param>
        <summary>
            Create a <see cref="T:Microsoft.ML.Transforms.OneHotEncodingEstimator" />, which converts the input column specified by <paramref name="inputColumnName" />
            into a column of one-hot encoded vectors named <paramref name="outputColumnName" />.
            </summary>
        <returns>To be added.</returns>
        <remarks>To be added.</remarks>
        <example>
          <format type="text/markdown"><![CDATA[
             [!code-csharp[OneHotEncoding](~/../docs/samples/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Categorical/OneHotEncoding.cs)]
            ]]></format>
        </example>
      </Docs>
    </Member>
    <Member MemberName="OneHotHashEncoding">
      <MemberSignature Language="C#" Value="public static Microsoft.ML.Transforms.OneHotHashEncodingEstimator OneHotHashEncoding (this Microsoft.ML.TransformsCatalog.CategoricalTransforms catalog, Microsoft.ML.InputOutputColumnPair[] columns, Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind outputKind = Microsoft.ML.Transforms.OneHotEncodingEstimator+OutputKind.Indicator, int numberOfBits = 16, uint seed = 314489979, bool useOrderedHashing = true, int maximumNumberOfInverts = 0);" />
      <MemberSignature Language="ILAsm" Value=".method public static hidebysig class Microsoft.ML.Transforms.OneHotHashEncodingEstimator OneHotHashEncoding(class Microsoft.ML.TransformsCatalog/CategoricalTransforms catalog, class Microsoft.ML.InputOutputColumnPair[] columns, valuetype Microsoft.ML.Transforms.OneHotEncodingEstimator/OutputKind outputKind, int32 numberOfBits, unsigned int32 seed, bool useOrderedHashing, int32 maximumNumberOfInverts) cil managed" />
      <MemberSignature Language="DocId" Value="M:Microsoft.ML.CategoricalCatalog.OneHotHashEncoding(Microsoft.ML.TransformsCatalog.CategoricalTransforms,Microsoft.ML.InputOutputColumnPair[],Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind,System.Int32,System.UInt32,System.Boolean,System.Int32)" />
      <MemberSignature Language="VB.NET" Value="&lt;Extension()&gt;&#xA;Public Function OneHotHashEncoding (catalog As TransformsCatalog.CategoricalTransforms, columns As InputOutputColumnPair(), Optional outputKind As OneHotEncodingEstimator.OutputKind = Microsoft.ML.Transforms.OneHotEncodingEstimator+OutputKind.Indicator, Optional numberOfBits As Integer = 16, Optional seed As UInteger = 314489979, Optional useOrderedHashing As Boolean = true, Optional maximumNumberOfInverts As Integer = 0) As OneHotHashEncodingEstimator" />
      <MemberSignature Language="F#" Value="static member OneHotHashEncoding : Microsoft.ML.TransformsCatalog.CategoricalTransforms * Microsoft.ML.InputOutputColumnPair[] * Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind * int * uint32 * bool * int -&gt; Microsoft.ML.Transforms.OneHotHashEncodingEstimator" Usage="Microsoft.ML.CategoricalCatalog.OneHotHashEncoding (catalog, columns, outputKind, numberOfBits, seed, useOrderedHashing, maximumNumberOfInverts)" />
      <MemberType>Method</MemberType>
      <AssemblyInfo>
        <AssemblyName>Microsoft.ML.Transforms</AssemblyName>
        <AssemblyVersion>1.0.0.0</AssemblyVersion>
      </AssemblyInfo>
      <ReturnValue>
        <ReturnType>Microsoft.ML.Transforms.OneHotHashEncodingEstimator</ReturnType>
      </ReturnValue>
      <Parameters>
        <Parameter Name="catalog" Type="Microsoft.ML.TransformsCatalog+CategoricalTransforms" RefType="this" />
        <Parameter Name="columns" Type="Microsoft.ML.InputOutputColumnPair[]" />
        <Parameter Name="outputKind" Type="Microsoft.ML.Transforms.OneHotEncodingEstimator+OutputKind" />
        <Parameter Name="numberOfBits" Type="System.Int32" />
        <Parameter Name="seed" Type="System.UInt32" />
        <Parameter Name="useOrderedHashing" Type="System.Boolean" />
        <Parameter Name="maximumNumberOfInverts" Type="System.Int32" />
      </Parameters>
      <Docs>
        <param name="catalog">The transform catalog</param>
        <param name="columns">The pairs of input and output columns. The output columns' data type will be a vector of <see cref="T:System.Single" /> if <paramref name="outputKind" /> is
            <see cref="F:Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind.Bag" />, <see cref="F:Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind.Indicator" />, and <see cref="F:Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind.Binary" />.
            If <paramref name="outputKind" /> is <see cref="F:Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind.Key" />, the output columns' data type will be a key in the case of scalar input column
            or a vector of keys in the case of a vector input column.</param>
        <param name="outputKind">The conversion mode.</param>
        <param name="numberOfBits">Number of bits to hash into. Must be between 1 and 30, inclusive.</param>
        <param name="seed">Hashing seed.</param>
        <param name="useOrderedHashing">Whether the position of each term should be included in the hash.</param>
        <param name="maximumNumberOfInverts">During hashing we constuct mappings between original values and the produced hash values.
            Text representation of original values are stored in the slot names of the  metadata for the new column. Hashing, as such, can map many initial values to one.
            <paramref name="maximumNumberOfInverts" /> specifies the upper bound of the number of distinct input values mapping to a hash that should be retained.
            <value>0</value> does not retain any input values. <value>-1</value> retains all input values mapping to each hash.</param>
        <summary>
            Create a <see cref="T:Microsoft.ML.Transforms.OneHotHashEncodingEstimator" />, which converts one or more input text columns specified by <paramref name="columns" />
            into as many columns of hash-based one-hot encoded vectors.
            </summary>
        <returns>To be added.</returns>
        <remarks>If multiple columns are passed to the estimator, all of the columns will be processed in a single pass over the data.
            Therefore, it is more efficient to specify one estimator with many columns than it is to specify many estimators each with a single column.
            </remarks>
        <example>
          <format type="text/markdown"><![CDATA[
             [!code-csharp[OneHotHashEncoding](~/../docs/samples/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Categorical/OneHotHashEncodingMultiColumn.cs)]
            ]]></format>
        </example>
      </Docs>
    </Member>
    <Member MemberName="OneHotHashEncoding">
      <MemberSignature Language="C#" Value="public static Microsoft.ML.Transforms.OneHotHashEncodingEstimator OneHotHashEncoding (this Microsoft.ML.TransformsCatalog.CategoricalTransforms catalog, string outputColumnName, string inputColumnName = default, Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind outputKind = Microsoft.ML.Transforms.OneHotEncodingEstimator+OutputKind.Indicator, int numberOfBits = 16, uint seed = 314489979, bool useOrderedHashing = true, int maximumNumberOfInverts = 0);" />
      <MemberSignature Language="ILAsm" Value=".method public static hidebysig class Microsoft.ML.Transforms.OneHotHashEncodingEstimator OneHotHashEncoding(class Microsoft.ML.TransformsCatalog/CategoricalTransforms catalog, string outputColumnName, string inputColumnName, valuetype Microsoft.ML.Transforms.OneHotEncodingEstimator/OutputKind outputKind, int32 numberOfBits, unsigned int32 seed, bool useOrderedHashing, int32 maximumNumberOfInverts) cil managed" />
      <MemberSignature Language="DocId" Value="M:Microsoft.ML.CategoricalCatalog.OneHotHashEncoding(Microsoft.ML.TransformsCatalog.CategoricalTransforms,System.String,System.String,Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind,System.Int32,System.UInt32,System.Boolean,System.Int32)" />
      <MemberSignature Language="VB.NET" Value="&lt;Extension()&gt;&#xA;Public Function OneHotHashEncoding (catalog As TransformsCatalog.CategoricalTransforms, outputColumnName As String, Optional inputColumnName As String = Nothing, Optional outputKind As OneHotEncodingEstimator.OutputKind = Microsoft.ML.Transforms.OneHotEncodingEstimator+OutputKind.Indicator, Optional numberOfBits As Integer = 16, Optional seed As UInteger = 314489979, Optional useOrderedHashing As Boolean = true, Optional maximumNumberOfInverts As Integer = 0) As OneHotHashEncodingEstimator" />
      <MemberSignature Language="F#" Value="static member OneHotHashEncoding : Microsoft.ML.TransformsCatalog.CategoricalTransforms * string * string * Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind * int * uint32 * bool * int -&gt; Microsoft.ML.Transforms.OneHotHashEncodingEstimator" Usage="Microsoft.ML.CategoricalCatalog.OneHotHashEncoding (catalog, outputColumnName, inputColumnName, outputKind, numberOfBits, seed, useOrderedHashing, maximumNumberOfInverts)" />
      <MemberType>Method</MemberType>
      <AssemblyInfo>
        <AssemblyName>Microsoft.ML.Transforms</AssemblyName>
        <AssemblyVersion>1.0.0.0</AssemblyVersion>
      </AssemblyInfo>
      <ReturnValue>
        <ReturnType>Microsoft.ML.Transforms.OneHotHashEncodingEstimator</ReturnType>
      </ReturnValue>
      <Parameters>
        <Parameter Name="catalog" Type="Microsoft.ML.TransformsCatalog+CategoricalTransforms" RefType="this" />
        <Parameter Name="outputColumnName" Type="System.String" />
        <Parameter Name="inputColumnName" Type="System.String" />
        <Parameter Name="outputKind" Type="Microsoft.ML.Transforms.OneHotEncodingEstimator+OutputKind" />
        <Parameter Name="numberOfBits" Type="System.Int32" />
        <Parameter Name="seed" Type="System.UInt32" />
        <Parameter Name="useOrderedHashing" Type="System.Boolean" />
        <Parameter Name="maximumNumberOfInverts" Type="System.Int32" />
      </Parameters>
      <Docs>
        <param name="catalog">The transform catalog.</param>
        <param name="outputColumnName">Name of the column resulting from the transformation of <paramref name="inputColumnName" />.
            This column's data type will be a vector of <see cref="T:System.Single" /> if <paramref name="outputKind" /> is
            <see cref="F:Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind.Bag" />, <see cref="F:Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind.Indicator" />, and <see cref="F:Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind.Binary" />.
            If <paramref name="outputKind" /> is <see cref="F:Microsoft.ML.Transforms.OneHotEncodingEstimator.OutputKind.Key" />, this column's data type will be a key in the case of a scalar input column
            or a vector of keys in the case of a vector input column. </param>
        <param name="inputColumnName">Name of column to transform. If set to <see langword="null" />, the value of the <paramref name="outputColumnName" /> will be used as source.
            This column's data type can be scalar or vector of numeric, text, boolean, <see cref="T:System.DateTime" /> or <see cref="T:System.DateTimeOffset" />.</param>
        <param name="outputKind">The conversion mode.</param>
        <param name="numberOfBits">Number of bits to hash into. Must be between 1 and 30, inclusive.</param>
        <param name="seed">Hashing seed.</param>
        <param name="useOrderedHashing">Whether the position of each term should be included in the hash.</param>
        <param name="maximumNumberOfInverts">During hashing we constuct mappings between original values and the produced hash values.
            Text representation of original values are stored in the slot names of the  metadata for the new column.Hashing, as such, can map many initial values to one.
            <paramref name="maximumNumberOfInverts" /> specifies the upper bound of the number of distinct input values mapping to a hash that should be retained.
            <value>0</value> does not retain any input values. <value>-1</value> retains all input values mapping to each hash.</param>
        <summary>
            Create a <see cref="T:Microsoft.ML.Transforms.OneHotHashEncodingEstimator" />, which converts a text column specified by <paramref name="inputColumnName" />
            into a hash-based one-hot encoded vector column named <paramref name="outputColumnName" />.
            </summary>
        <returns>To be added.</returns>
        <remarks>To be added.</remarks>
        <example>
          <format type="text/markdown"><![CDATA[
             [!code-csharp[OneHotHashEncoding](~/../docs/samples/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Categorical/OneHotHashEncoding.cs)]
            ]]></format>
        </example>
      </Docs>
    </Member>
  </Members>
</Type>