Update xml documentation for ProduceHashedNgrams (#3419)

Author: Ivanidzo4ka

src/Microsoft.ML.Transforms/Text/NgramHashingTransformer.cs

@@ -29,10 +29,7 @@
 
 namespace Microsoft.ML.Transforms.Text
 {
-    /// <summary>
-    /// Produces a bag of counts of ngrams (sequences of consecutive words of length 1-n) in a given text.
-    /// It does so by hashing each ngram and using the hash value as the index in the bag.
-    /// </summary>
+    /// <see cref="ITransformer"/> resulting from fitting a <see cref="NgramHashingEstimator"/>.
     public sealed class NgramHashingTransformer : RowToRowTransformerBase
     {
         internal sealed class Column : ManyToOneColumn
@@ -861,12 +858,28 @@ public VBuffer<ReadOnlyMemory<char>>[] SlotNamesMetadata(out VectorDataViewType[
     }
 
     /// <summary>
-    /// Produces a bag of counts of ngrams (sequences of consecutive words of length 1-n) in a given text.
-    /// It does so by hashing each ngram and using the hash value as the index in the bag.
-    ///
-    /// <see cref="NgramHashingEstimator"/> is different from <see cref="WordHashBagEstimator"/> in a way that <see cref="NgramHashingEstimator"/>
-    /// takes tokenized text as input while <see cref="WordHashBagEstimator"/> tokenizes text internally.
+    /// <see cref="IEstimator{TTransformer}"/> for the <see cref="NgramHashingTransformer"/>.
     /// </summary>
+    /// <remarks>
+    /// <format type="text/markdown"><![CDATA[
+    /// ###  Estimator Characteristics
+    /// |  |  |
+    /// | -- | -- |
+    /// | Does this estimator need to look at the data to train its parameters? | Yes |
+    /// | Input column data type | Vector of [Key](<xref:Microsoft.ML.Data.KeyDataViewType>) |
+    /// | Output column data type | Vector of known size of <xref:System.Single> |
+    ///
+    /// The resulting <xref:Microsoft.ML.Transforms.Text.NgramHashingTransformer/> creates a new column, named as specified in the output column name parameters, and
+    /// produces a vector of counts of n-grams (sequences of consecutive words of length 1-n) from a given data.
+    /// It does so by hashing each n-gram and using the hash value as the index in the bag.
+    ///
+    /// <xref:Microsoft.ML.Transforms.Text.NgramHashingEstimator> is different from <xref:Microsoft.ML.Transforms.Text.WordHashBagEstimator>
+    /// in a way that The former takes tokenized text as input while the latter tokenizes text internally.
+    /// See the See Also section for links to examples of the usage.
+    /// ]]>
+    /// </format>
+    /// </remarks>
+    /// <seealso cref="TextCatalog.ProduceHashedNgrams(TransformsCatalog.TextTransforms, string, string, int, int, int, bool, uint, bool, int, bool)" />
     public sealed class NgramHashingEstimator : IEstimator<NgramHashingTransformer>
     {
         /// <summary>

src/Microsoft.ML.Transforms/Text/TextCatalog.cs

@@ -403,15 +403,18 @@ public static WordHashBagEstimator ProduceHashedWordBags(this TransformsCatalog.
                 maximumNumberOfInverts: maximumNumberOfInverts);
 
         /// <summary>
-        /// Produces a bag of counts of hashed ngrams in <paramref name="inputColumnName"/>
-        /// and outputs ngram vector as <paramref name="outputColumnName"/>
-        ///
+        /// Create a <see cref="NgramHashingEstimator"/>, which copies the data from the column specified in <paramref name="inputColumnName"/>
+        /// to a new column: <paramref name="outputColumnName"/> and produces a vector of counts of hashed n-grams.
+        /// </summary>
+        /// <remarks>
         /// <see cref="NgramHashingEstimator"/> is different from <see cref="WordHashBagEstimator"/> in a way that <see cref="NgramHashingEstimator"/>
         /// takes tokenized text as input while <see cref="WordHashBagEstimator"/> tokenizes text internally.
-        /// </summary>
-        /// <param name="catalog">The text-related transform's catalog.</param>
-        /// <param name="outputColumnName">Name of the column resulting from the transformation of <paramref name="inputColumnName"/>.</param>
-        /// <param name="inputColumnName">Name of the column to transform. If set to <see langword="null"/>, the value of the <paramref name="outputColumnName"/> will be used as source.</param>
+        /// </remarks>
+        /// <param name="catalog">The transform's catalog.</param>
+        /// <param name="outputColumnName">Name of the column resulting from the transformation of <paramref name="inputColumnName"/>.
+        /// This column's data type will be vector of <see cref="System.Single"/>.</param>
+        /// <param name="inputColumnName">Name of the column to copy the data from.
+        /// This estimator operates over vector of key type.</param>
         /// <param name="numberOfBits">Number of bits to hash into. Must be between 1 and 30, inclusive.</param>
         /// <param name="ngramLength">Ngram length.</param>
         /// <param name="skipLength">Maximum number of tokens to skip when constructing an ngram.</param>
@@ -439,15 +442,18 @@ public static NgramHashingEstimator ProduceHashedNgrams(this TransformsCatalog.T
                 useAllLengths: useAllLengths, numberOfBits: numberOfBits, seed: seed, useOrderedHashing: useOrderedHashing, maximumNumberOfInverts: maximumNumberOfInverts, rehashUnigrams) });
 
         /// <summary>
-        /// Produces a bag of counts of hashed ngrams in <paramref name="inputColumnNames"/>
-        /// and outputs ngram vector as <paramref name="outputColumnName"/>
-        ///
+        /// Create a <see cref="NgramHashingEstimator"/>, which takes the data from the multiple columns specified in <paramref name="inputColumnNames"/>
+        /// to a new column: <paramref name="outputColumnName"/> and produces a vector of counts of hashed n-grams.
+        /// </summary>
+        /// <remarks>
         /// <see cref="NgramHashingEstimator"/> is different from <see cref="WordHashBagEstimator"/> in a way that <see cref="NgramHashingEstimator"/>
         /// takes tokenized text as input while <see cref="WordHashBagEstimator"/> tokenizes text internally.
-        /// </summary>
-        /// <param name="catalog">The text-related transform's catalog.</param>
-        /// <param name="outputColumnName">Name of the column resulting from the transformation of <paramref name="inputColumnNames"/>.</param>
-        /// <param name="inputColumnNames">Names of the columns to transform. If set to <see langword="null"/>, the value of the <paramref name="outputColumnName"/> will be used as source.</param>
+        /// </remarks>
+        /// <param name="catalog">The transform's catalog.</param>
+        /// <param name="outputColumnName">Name of the column resulting from the transformation of <paramref name="inputColumnNames"/>.
+        /// This column's data type will be vector of known size of <see cref="System.Single"/>.</param>
+        /// <param name="inputColumnNames">Name of the multiple columns to take the data from.
+        /// This estimator operates over vector of key type.</param>
         /// <param name="numberOfBits">Number of bits to hash into. Must be between 1 and 30, inclusive.</param>
         /// <param name="ngramLength">Ngram length.</param>
         /// <param name="skipLength">Maximum number of tokens to skip when constructing an ngram.</param>