Fix some SDCA documentation issues (#3533)

* Fix some SDCA documentation issues

* Remove empty lines

* Add empty lines

Author: yaeldMS

docs/api-reference/algo-details-sdca.md

@@ -39,11 +39,11 @@ error of the hypothesis. An accurate model with extreme coefficient values would
 be penalized more, but a less accurate model with more conservative values would
 be penalized less. This learner supports [elastic net
 regularization](https://en.wikipedia.org/wiki/Elastic_net_regularization): a
-linear combination of L1-norm (LASSO), $|| \boldsymbol{w} ||_1$, and L2-norm
-(ridge), $|| \boldsymbol{w} ||_2^2$ regularizations. L1-nrom and L2-norm
+linear combination of L1-norm (LASSO), $|| \textbf{w} ||_1$, and L2-norm
+(ridge), $|| \textbf{w} ||_2^2$ regularizations. L1-nrom and L2-norm
 regularizations have different effects and uses that are complementary in
 certain respects. Using L1-norm can increase sparsity of the trained
-$\boldsymbol{w}$. When working with high-dimensional data, it shrinks small
+$\textbf{w}$. When working with high-dimensional data, it shrinks small
 weights of irrevalent features to 0 and therefore no reource will be spent on
 those bad features when making prediction. L2-norm regularization is preferable
 for data that is not sparse and it largely penalizes the existence of large

docs/api-reference/io-columns-binary-classification.md

@@ -1,6 +1,8 @@
 ### Input and Output Columns
 The input label column data must be <xref:System.Boolean>.
-The input features column data must be a known-sized vector of <xref:System.Single>. This trainer outputs the following columns:
+The input features column data must be a known-sized vector of <xref:System.Single>.
+
+This trainer outputs the following columns:
 
 | Output Column Name | Column Type | Description|
 | -- | -- | -- |

docs/api-reference/io-columns-regression.md

@@ -1,5 +1,8 @@
 ### Input and Output Columns
-The input label column data must be <xref:System.Single>. This trainer outputs the following columns:
+The input label column data must be <xref:System.Single>.
+The input features column data must be a known-sized vector of <xref:System.Single>.
+
+This trainer outputs the following columns:
 
 | Output Column Name | Column Type | Description|
 | -- | -- | -- |

src/Microsoft.ML.StandardTrainers/Standard/SdcaBinary.cs

@@ -1651,7 +1651,7 @@ private protected override SchemaShape.Column[] ComputeSdcaBinaryClassifierSchem
     /// | Is caching required? | No |
     /// | Required NuGet in addition to Microsoft.ML | None |
     ///
-    /// [!include[algorithm](~/../docs/samples/docs/api-reference/algo-details-sdca.md)].
+    /// [!include[algorithm](~/../docs/samples/docs/api-reference/algo-details-sdca.md)]
     /// ]]>
     /// </format>
     /// </remarks>