..updating..

docs/samples/Microsoft.ML.Samples/Dynamic/ValueMapping.cs

@@ -15,7 +15,7 @@ class SampleInfertDataWithFeatures
         }
 
         /// This example demonstrates the use of the ValueMappingEstimator by mapping string-to-string values. This is useful
-        /// to map strings to a grouping. In this example, the Education data maps to the groups Undergraduate and Postgraduate:
+        /// to map strings to a grouping. In this example, the education data maps to the groups Undergraduate and Postgraduate:
         ///   0-5yrs  -> Undergraduate 
         ///   6-11yrs -> Postgraduate
         ///   12+yrs  -> Postgraduate

docs/samples/Microsoft.ML.Samples/Dynamic/ValueMappingFloatToString.cs

@@ -31,7 +31,6 @@ public static void Run()
             IDataView trainData = mlContext.Data.ReadFromEnumerable(data);
 
             // If the list of keys and values are known, they can be passed to the API. The ValueMappingEstimator can also get the mapping through an IDataView
-
             // Creating a list of keys based on the induced value from the dataset
             var temperatureKeys = new List<float>()
             {

docs/samples/Microsoft.ML.Samples/Dynamic/ValueMappingStringToArray.cs

@@ -21,9 +21,9 @@ class SampleInfertDataWithIntArray
         /// This example demonstrates the use of the ValueMappingEstimator by mapping string-to-array values which allows for mapping string data
         /// to numeric arrays that can then be used as a feature set for a trainer. In this example, we are mapping the education data to
         /// arbitrary integer arrays with the following association:
-        ///     0-5yrs  -> 1,2,3,4
-        ///     6-11yrs -> 5,6,7
-        ///     12+yrs  -> 42, 32
+        ///     0-5yrs  -> 1, 2, 3
+        ///     6-11yrs -> 5, 6, 7
+        ///     12+yrs  -> 42,32,64
         public static void Run()
         {
             // Create a new ML context, for ML.NET operations. It can be used for exception tracking and logging, 
@@ -35,7 +35,6 @@ public static void Run()
             IDataView trainData = mlContext.Data.ReadFromEnumerable(data);
 
             // If the list of keys and values are known, they can be passed to the API. The ValueMappingEstimator can also get the mapping through an IDataView
-
             // Creating a list of keys based on the Education values from the dataset
             var educationKeys = new List<string>()
             {
@@ -47,9 +46,9 @@ public static void Run()
             // Sample list of associated array values
             var educationValues = new List<int[]>()
             {
-                new int[] { 1,2,3,4 },
+                new int[] { 1,2,3 },
                 new int[] { 5,6,7 },
-                new int[] { 42, 32 }
+                new int[] { 42,32,64 }
             };
 
             // Constructs the ValueMappingEstimator making the ML.net pipeline
@@ -72,10 +71,10 @@ public static void Run()
             //
             // Example of mapping string->array
             // Age     Education   EducationFeature
-            // 26      0 - 5yrs    1,2,3,4
-            // 42      0 - 5yrs    1,2,3,4
-            // 39      12 + yrs    42,32
-            // 34      0 - 5yrs    1,2,3,4
+            // 26      0 - 5yrs    1,2,3
+            // 42      0 - 5yrs    1,2,3
+            // 39      12 + yrs    42,32,64
+            // 34      0 - 5yrs    1,2,3
             // 35      6 - 11yrs   5,6,7
         }
     }

docs/samples/Microsoft.ML.Samples/Dynamic/ValueMappingStringToKeyType.cs

@@ -23,7 +23,7 @@ class SampleInfertDataWithFeatures
         /// instead of the actual value provides a unique integer representation of the value. When the treatValueAsKeyTypes is true, 
         /// the ValueMappingEstimator will generate a KeyType for each unique value.
         /// 
-        /// In this example, the education data is mapped to a grouping of 'Undergraudate' and 'Postgraduate'. Because KeyTypes are used, the
+        /// In this example, the education data is mapped to a grouping of 'Undergraduate' and 'Postgraduate'. Because KeyTypes are used, the
         /// ValueMappingEstimator will output the KeyType value rather than string value of 'Undergraduate' or 'Postgraduate'.
         /// 
         /// The KeyToValueEstimator is added to the pipeline to convert the KeyType back to the original value. Therefore the output of this example 

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

@@ -136,7 +136,7 @@ public static ValueToKeyMappingEstimator MapValueToKey(this TransformsCatalog.Co
             => new ValueToKeyMappingEstimator(CatalogUtils.GetEnvironment(catalog), columns, keyData);
 
         /// <summary>
-        /// Maps specified keys to specified values
+        /// <see cref="ValueMappingEstimator"/>
         /// </summary>
         /// <typeparam name="TInputType">The key type.</typeparam>
         /// <typeparam name="TOutputType">The value type.</typeparam>
@@ -152,7 +152,6 @@ public static ValueToKeyMappingEstimator MapValueToKey(this TransformsCatalog.Co
         ///  [!code-csharp[ValueMappingEstimator](~/../docs/samples/docs/samples/Microsoft.ML.Samples/Dynamic/ValueMapping.cs)]
         /// ]]></format>
         /// </example>
-
         public static ValueMappingEstimator<TInputType, TOutputType> ValueMap<TInputType, TOutputType>(
             this TransformsCatalog.ConversionTransforms catalog,
             IEnumerable<TInputType> keys,
@@ -161,10 +160,7 @@ public static ValueMappingEstimator<TInputType, TOutputType> ValueMap<TInputType
             => new ValueMappingEstimator<TInputType, TOutputType>(CatalogUtils.GetEnvironment(catalog), keys, values, columns);
 
         /// <summary>
-        /// Maps the <paramref name="columns.input"/> using the keys in the dictionary to the values of dictionary i.e.
-        /// a value 'x' in the <paramref name="columns.input"/> would be mappped to a value stored in dictionary[x].
-        /// In this case, the <paramref name="lookupMap"/> is used to build up the dictionary where <paramref name="keyColumn"/>
-        /// and <paramref name="valueColumn"/> specify the keys and values of dictionary respectively.
+        /// <see cref="ValueMappingEstimator"/>
         /// </summary>
         /// <param name="catalog">The categorical transform's catalog</param>
         /// <param name="lookupMap">An instance of <see cref="IDataView"/> that contains the key and value columns.</param>

src/Microsoft.ML.Data/Transforms/doc.xml

@@ -72,18 +72,18 @@
         specific value. The ValueMappingEstimator supports keys and values of different <see cref="System.Type"/> to support different data types.
         Examples for using a ValueMappingEstimator are:
         <list>
-          <li>
+          <item>
             <description>Converting a string value to a string value, this can be useful for grouping (i.e. 'cat', 'dog', 'horse' maps to 'mammals')</description>
-          </li>
-          <li>
+          </item>
+          <item>
             <description>Converting a string value to a integer value (i.e. converting the text description like quality to an numeric where 'good' maps to 1, 'poor' maps to 0</description>
-          </li>
-          <li>
+          </item>
+          <item>
             <description>
               Converting a integer value to a string value and have the string value represented as a <see cref="KeyType"/>
               (i.e. convert zip codes to a state string value, which will generate a unique integer value that can be used as a label.
             </description>
-          </li>
+          </item>
         </list>
         Values can be repeated to allow for multiple keys to map to the same value, however keys can not be repeated. The mapping between keys and values
         can be specified either through lists, where the key list and value list must be the same size or can be done through an <see cref="IDataView"/>.