PR feedback.

Author: codemzs

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

@@ -49,8 +49,8 @@ namespace Microsoft.ML.Trainers
     /// ]]>
     /// </format>
     /// </remarks>
-    /// <seealso cref="Microsoft.ML.StandardTrainersCatalog.LbfgsPoissonRegression(Microsoft.ML.RegressionCatalog.RegressionTrainers,System.String,System.String,System.String,System.Single,System.Single,System.Single,System.Int32,System.Boolean)"/>
-    /// <seealso cref="Microsoft.ML.StandardTrainersCatalog.LbfgsPoissonRegression(Microsoft.ML.RegressionCatalog.RegressionTrainers,Microsoft.ML.Trainers.LbfgsPoissonRegressionTrainer.Options)"/>
+    /// <seealso cref="StandardTrainersCatalog.LbfgsPoissonRegression(RegressionCatalog.RegressionTrainers, string, string, string, float, float, float, int, bool)"/>
+    /// <seealso cref="StandardTrainersCatalog.LbfgsPoissonRegression(RegressionCatalog.RegressionTrainers, LbfgsPoissonRegressionTrainer.Options)"/>
     /// <seealso cref="Options"/>
     public sealed class LbfgsPoissonRegressionTrainer : LbfgsTrainerBase<LbfgsPoissonRegressionTrainer.Options, RegressionPredictionTransformer<PoissonRegressionModelParameters>, PoissonRegressionModelParameters>
     {
@@ -60,7 +60,8 @@ public sealed class LbfgsPoissonRegressionTrainer : LbfgsTrainerBase<LbfgsPoisso
         internal const string Summary = "Poisson Regression assumes the unknown function, denoted Y has a Poisson distribution.";
 
         /// <summary>
-        /// Options for the <see cref="LbfgsPoissonRegressionTrainer"/>.
+        /// Options for the <see cref="LbfgsPoissonRegressionTrainer"/> as used in
+        /// [LbfgsPoissonRegression(Options)](xref:Microsoft.ML.StandardTrainersCatalog.LbfgsPoissonRegression(Microsoft.ML.RegressionCatalog.RegressionTrainers,Microsoft.ML.Trainers.LbfgsPoissonRegressionTrainer.Options)).
         /// </summary>
         public sealed class Options : OptionsBase
         {

src/Microsoft.ML.StandardTrainers/StandardTrainersCatalog.cs

@@ -573,11 +573,11 @@ public static LbfgsLogisticRegressionBinaryTrainer LbfgsLogisticRegression(this
         }
 
         /// <summary>
-        /// Creates a <see cref="Microsoft.ML.Trainers.LbfgsPoissonRegressionTrainer"/>, which predicts a target using a linear regression model.
+        /// Create <see cref="LbfgsPoissonRegressionTrainer"/>, which predicts a target using a linear regression model.
         /// </summary>
         /// <param name="catalog">The regression catalog trainer object.</param>
-        /// <param name="labelColumnName">The name of the label column. The column data must be <see cref="System.Single"/></param>
-        /// <param name="featureColumnName">The name of the feature column. The column data must be a known-sized vector of <see cref="System.Single"/></param>
+        /// <param name="labelColumnName">The name of the label column. The column data must be <see cref="System.Single"/>.</param>
+        /// <param name="featureColumnName">The name of the feature column. The column data must be a known-sized vector of <see cref="System.Single"/>.</param>
         /// <param name="exampleWeightColumnName">The name of the example weight column (optional).</param>
         /// <param name="l1Regularization">The L1 <a href='https://en.wikipedia.org/wiki/Regularization_(mathematics)'>regularization</a> hyperparameter. Higher values will tend to lead to more sparse model.</param>
         /// <param name="l2Regularization">The L2 weight for <a href='https://en.wikipedia.org/wiki/Regularization_(mathematics)'>regularization</a>.</param>
@@ -606,7 +606,7 @@ public static LbfgsPoissonRegressionTrainer LbfgsPoissonRegression(this Regressi
         }
 
         /// <summary>
-        /// Creates a <see cref="Microsoft.ML.Trainers.LbfgsPoissonRegressionTrainer"/>, which predicts a target using a linear regression model with advanced options.
+        /// Create <see cref="LbfgsPoissonRegressionTrainer"/> using advanced options, which predicts a target using a linear regression model.
         /// </summary>
         /// <param name="catalog">The regression catalog trainer object.</param>
         /// <param name="options">Trainer options.</param>