Fix broken xrefs across code base. (#3557)

* Fix broke xrefs across codebase.

* backtick.

Author: codemzs

src/Microsoft.ML.Transforms/CountFeatureSelection.cs

@@ -32,7 +32,7 @@ namespace Microsoft.ML.Transforms
     /// | Output column data type | Same as the input column.|
     ///
     /// This transform uses a set of aggregators to count the number of non-default values for each slot(vector element) and
-    /// instantiates a <xref:Microsoft.ML.Transforms.SlotsDroppingTransformer> to actually drop the slots that have the default values for the types
+    /// instantiates a transformer to actually drop the slots that have the default values for the types
     /// keeping at least 'count' non-default values.
     /// This transform is useful when applied together with a <xref:Microsoft.ML.Transforms.OneHotHashEncodingTransformer>.
     /// The count feature selection can remove the features generated by the hash transform that have no data in the examples.

src/Microsoft.ML.Transforms/CustomMappingTransformer.cs

@@ -213,7 +213,7 @@ public ITransformer GetTransformer()
     /// | Input column data type | Any |
     /// | Output column data type | Any |
     ///
-    /// The resulting <xref:Microsoft.ML.Transforms.CustomMappingTransformer> applies a user defined mapping
+    /// The resulting <xref:Microsoft.ML.Transforms.CustomMappingTransformer`2> applies a user defined mapping
     /// to one or more input columns and produces one or more output columns. This transformation doesn't change the number of rows,
     /// and can be seen as the result of applying the user's function to every row of the input data.
     ///

src/Microsoft.ML.Transforms/MissingValueIndicatorTransformer.cs

@@ -441,7 +441,7 @@ private void FillValues(int srcLength, ref VBuffer<bool> dst, List<int> indices,
     /// | Input column data type | Vector or scalar value of <xref:System.Single> or <xref:System.Double> |
     /// | Output column data type | If input column was scalar then <xref:System.Boolean> otherwise vector of <xref:System.Boolean>. |
     ///
-    /// The resulting <xref:Microsoft.ML.Transfroms.MissingValueIndicatorTransformer/> creates a new column, named as specified in the output column name parameters, and
+    /// The resulting <xref:Microsoft.ML.Transforms.MissingValueIndicatorTransformer> creates a new column, named as specified in the output column name parameters, and
     /// fills it with vector of bools where `true` in the i-th position in array indicates the i-th element in input column has missing value and `false` otherwise.
     /// Check the See Also section for links of examples of the usage.
     /// ]]>

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

@@ -869,7 +869,7 @@ public VBuffer<ReadOnlyMemory<char>>[] SlotNamesMetadata(out VectorDataViewType[
     /// | 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
+    /// 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 n-gram counts (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.
     ///

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

@@ -491,7 +491,7 @@ private protected override Func<int, bool> GetDependenciesCore(Func<int, bool> a
     /// | Input column data type | Vector of [Text](xref:Microsoft.ML.Data.TextDataViewType) |
     /// | Output column data type | Variable-sized vector of [Text](xref:Microsoft.ML.Data.TextDataViewType) |
     ///
-    /// The resulting <xref:Microsoft.ML.Transforms.Text.StopWordsRemovingTransformer/> creates a new column, named as specified in the output column name parameter,
+    /// The resulting <xref:Microsoft.ML.Transforms.Text.StopWordsRemovingTransformer> creates a new column, named as specified in the output column name parameter,
     /// and fills it with a vector of words containing all of the words in the input column **except the predefined list of stopwords for the specified language.
     /// All text comparison made by casting predefined text and text from input column to lower case using casing rules of invariant culture.
     /// Check the See Also section for links to examples of the usage.
@@ -1097,7 +1097,7 @@ protected override Delegate MakeGetter(DataViewRow input, int iinfo, Func<int, b
     /// | Input column data type | Vector of [Text](xref:Microsoft.ML.Data.TextDataViewType) |
     /// | Output column data type | Unknown-sized vector of [Text](xref:Microsoft.ML.Data.TextDataViewType) |
     ///
-    /// The resulting <xref:Microsoft.ML.Transforms.Text.CustomStopWordsRemovingTransformer/> creates a new column, named as specified by the output column name parameter, and
+    /// The resulting <xref:Microsoft.ML.Transforms.Text.CustomStopWordsRemovingTransformer> creates a new column, named as specified by the output column name parameter, and
     /// fills it with a vector of words containing all of the words in the input column except those given by the stopwords parameter.
     /// All text comparison made by casting provided words and words from input column to lower case using casing rules of invariant culture.
     /// Check the See Also section for links to examples of the usage.

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

@@ -55,8 +55,8 @@ public interface IStopWordsRemoverOptions { }
     /// * [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.
-    ///  To output an additional column with the tokens generated, use [OutputTokensColumnName](xref: Microsoft.ML.Transforms.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.TextFeaturizingEstimator.Options>, where the estimator can be further tuned.
+    ///  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.
     /// ]]></format>
     /// </remarks>
     /// <seealso cref="TextCatalog.FeaturizeText(TransformsCatalog.TextTransforms, string, Options, string[])"/>