Reorder MatrixFactorizationTrainer parameters (#2561)

* Reorder MatrixFactorizationTrainer parameters

* nit

* PR feedback

Author: najeeb-kazmi

docs/samples/Microsoft.ML.Samples/Dynamic/Trainers/Recommendation/MatrixFactorization.cs

@@ -26,8 +26,8 @@ public static void Example()
             // Create a matrix factorization trainer which may consume "Value" as the training label, "MatrixColumnIndex" as the
             // matrix's column index, and "MatrixRowIndex" as the matrix's row index. Here nameof(...) is used to extract field
             // names' in MatrixElement class.
-            var pipeline = mlContext.Recommendation().Trainers.MatrixFactorization(nameof(MatrixElement.MatrixColumnIndex),
-                nameof(MatrixElement.MatrixRowIndex), nameof(MatrixElement.Value), 10, 0.2, 10);
+            var pipeline = mlContext.Recommendation().Trainers.MatrixFactorization(nameof(MatrixElement.Value), nameof(MatrixElement.MatrixColumnIndex),
+                nameof(MatrixElement.MatrixRowIndex), 10, 0.2, 10);
 
             // Train a matrix factorization model.
             var model = pipeline.Fit(dataView);

src/Microsoft.ML.Recommender/MatrixFactorizationTrainer.cs

@@ -350,17 +350,17 @@ internal MatrixFactorizationTrainer(IHostEnvironment env, Options options)
         /// Initializes a new instance of <see cref="MatrixFactorizationTrainer"/>.
         /// </summary>
         /// <param name="env">The private instance of <see cref="IHostEnvironment"/>.</param>
+        /// <param name="labelColumnName">The name of the label column.</param>
         /// <param name="matrixColumnIndexColumnName">The name of the column hosting the matrix's column IDs.</param>
         /// <param name="matrixRowIndexColumnName">The name of the column hosting the matrix's row IDs.</param>
-        /// <param name="labelColumn">The name of the label column.</param>
         /// <param name="approximationRank">Rank of approximation matrixes.</param>
         /// <param name="learningRate">Initial learning rate. It specifies the speed of the training algorithm.</param>
         /// <param name="numIterations">Number of training iterations.</param>
         [BestFriend]
         internal MatrixFactorizationTrainer(IHostEnvironment env,
+            string labelColumnName,
             string matrixColumnIndexColumnName,
             string matrixRowIndexColumnName,
-            string labelColumn = DefaultColumnNames.Label,
             int approximationRank = Defaults.ApproximationRank,
             double learningRate = Defaults.LearningRate,
             int numIterations = Defaults.NumIterations)
@@ -383,7 +383,7 @@ internal MatrixFactorizationTrainer(IHostEnvironment env,
 
             _info = new TrainerInfo(normalization: false, caching: false);
 
-            LabelName = labelColumn;
+            LabelName = labelColumnName;
             MatrixColumnIndexName = matrixColumnIndexColumnName;
             MatrixRowIndexName = matrixRowIndexColumnName;
         }

src/Microsoft.ML.Recommender/RecommenderCatalog.cs

@@ -50,9 +50,9 @@ internal RecommendationTrainers(RecommendationCatalog catalog)
             /// and the value at the location specified by the two indexes.
             /// </para>
             /// </remarks>
+            /// <param name="labelColumn">The name of the label column.</param>
             /// <param name="matrixColumnIndexColumnName">The name of the column hosting the matrix's column IDs.</param>
             /// <param name="matrixRowIndexColumnName">The name of the column hosting the matrix's row IDs.</param>
-            /// <param name="labelColumn">The name of the label column.</param>
             /// <param name="approximationRank">Rank of approximation matrixes.</param>
             /// <param name="learningRate">Initial learning rate. It specifies the speed of the training algorithm.</param>
             /// <param name="numberOfIterations">Number of training iterations.</param>
@@ -63,13 +63,13 @@ internal RecommendationTrainers(RecommendationCatalog catalog)
             /// ]]></format>
             /// </example>
             public MatrixFactorizationTrainer MatrixFactorization(
+                string labelColumn,
                 string matrixColumnIndexColumnName,
                 string matrixRowIndexColumnName,
-                string labelColumn = DefaultColumnNames.Label,
                 int approximationRank = MatrixFactorizationTrainer.Defaults.ApproximationRank,
                 double learningRate = MatrixFactorizationTrainer.Defaults.LearningRate,
                 int numberOfIterations = MatrixFactorizationTrainer.Defaults.NumIterations)
-                    => new MatrixFactorizationTrainer(Owner.Environment, matrixColumnIndexColumnName, matrixRowIndexColumnName, labelColumn,
+                    => new MatrixFactorizationTrainer(Owner.Environment, labelColumn, matrixColumnIndexColumnName, matrixRowIndexColumnName,
                         approximationRank, learningRate, numberOfIterations);
 
             /// <summary>