CI Update

Author: VSC-Service-Account

dotnet/xml/FrameworksIndex/ml-dotnet-preview.xml

@@ -15,7 +15,29 @@
     <summary>
             Specifies a simple data type.
             </summary>
-    <remarks>To be added.</remarks>
+    <remarks>
+      <format type="text/markdown"><![CDATA[
+             Some transforms use the default value and/or missing value of the data types.
+             The table below shows the default value definition for each of the data types.
+            
+             | Type | Default Value | IsDefault Indicator |
+             | -- | -- | -- |
+             | <xref:Microsoft.ML.Data.DataKind.String> or [text](xref:Microsoft.ML.Data.TextDataViewType) | Empty or `null` string (both result in empty `System.ReadOnlyMemory<char>` | <xref:"System.ReadOnlyMemory`1.IsEmpty*> |
+             | [Key](xref:Microsoft.ML.Data.KeyDataViewType) type (supported by the unsigned integer types in `DataKind`) | Not defined | Always `false` |
+             | All other types | Default value of the corresponding system type as defined by .NET standard. In C#, default value expression `default(T)` provides that value. | Equality test with the default value |
+            
+             The table below shows the missing value definition for each of the data types.
+            
+             | Type | Missing Value | IsMissing Indicator |
+             | -- | -- | -- |
+             | <xref:Microsoft.ML.Data.DataKind.String> or [text](xref:Microsoft.ML.Data.TextDataViewType) | Not defined | Always `false` |
+             | [Key](xref:Microsoft.ML.Data.KeyDataViewType) type (supported by the unsigned integer types in `DataKind`) | `0` | Equality test with `0` |
+             | <xref:Microsoft.ML.Data.DataKind.Single> | <xref:System.Single.NaN> | <xref:System.Single.IsNaN(System.Single)> |
+             | <xref:Microsoft.ML.Data.DataKind.Double> | <xref:System.Double.NaN> | <xref:System.Double.IsNaN(System.Double)> |
+             | All other types | Not defined | Always `false` |
+            
+             ]]></format>
+    </remarks>
   </Docs>
   <Members>
     <Member MemberName="Boolean">

dotnet/xml/FrameworksIndex/ml-dotnet.xml

@@ -172,10 +172,9 @@
             </summary>
         <value>To be added.</value>
         <remarks>
-            The log-loss metric, is computed as follows:
-            LL = - (1/m) * sum( log(p[i]))
-            where m is the number of instances in the test set.
-            p[i] is the probability returned by the classifier if the instance belongs to the class,
+            The log-loss metric is computed as $-\frac{1}{m} \sum_{i=1}^m \log(p_i)$,
+            where $m$ is the number of instances in the test set.
+            $p_i$ is the probability returned by the classifier if the instance belongs to the class,
             and 1 minus the probability returned by the classifier if the instance does not belong to the class.
             </remarks>
         <example>