Default the kfolds to value 5 in CLI generated code (dotnet#115)

* Added sequential grouping of columns

* reverted the file

* Set up CI with Azure Pipelines

* Update azure-pipelines.yml for Azure Pipelines

* Update azure-pipelines.yml for Azure Pipelines

* remove file

* added kfold param and defaulted to value

* changed type

* added for regression

Author: srsaggam

src/mlnet/Templates/MLCodeGen.cs

@@ -133,16 +133,18 @@ private static ITransformer BuildTrainEvaluateAndSaveModel(MLContext mlContext)
 if("BinaryClassification".Equals(TaskType)){ 
             this.Write("            var crossValidationResults = mlContext.");
             this.Write(this.ToStringHelper.ToStringWithCulture(TaskType));
-            this.Write(".CrossValidateNonCalibrated(trainingDataView, trainingPipeline, numFolds: 3, labe" +
-                    "lColumn:\"Label\");\r\n            ConsoleHelper.PrintBinaryClassificationFoldsAvera" +
-                    "geMetrics(trainer.ToString(), crossValidationResults);\r\n");
+            this.Write(".CrossValidateNonCalibrated(trainingDataView, trainingPipeline, numFolds: ");
+            this.Write(this.ToStringHelper.ToStringWithCulture(Kfolds));
+            this.Write(", labelColumn:\"Label\");\r\n            ConsoleHelper.PrintBinaryClassificationFolds" +
+                    "AverageMetrics(trainer.ToString(), crossValidationResults);\r\n");
 }
 if("Regression".Equals(TaskType)){ 
             this.Write("            var crossValidationResults = mlContext.");
             this.Write(this.ToStringHelper.ToStringWithCulture(TaskType));
-            this.Write(".CrossValidate(trainingDataView, trainingPipeline, numFolds: 3, labelColumn:\"Labe" +
-                    "l\");\r\n            ConsoleHelper.PrintRegressionFoldsAverageMetrics(trainer.ToStr" +
-                    "ing(), crossValidationResults);\r\n");
+            this.Write(".CrossValidate(trainingDataView, trainingPipeline, numFolds: ");
+            this.Write(this.ToStringHelper.ToStringWithCulture(Kfolds));
+            this.Write(", labelColumn:\"Label\");\r\n            ConsoleHelper.PrintRegressionFoldsAverageMet" +
+                    "rics(trainer.ToString(), crossValidationResults);\r\n");
 }
  } 
             this.Write(@"
@@ -249,6 +251,7 @@ private static void TestSinglePrediction(MLContext mlContext)
 public bool AllowQuoting {get;set;}
 public bool AllowSparse {get;set;}
 public bool TrimWhiteSpace {get;set;} 
+public int Kfolds {get;set;} = 5;
 
     }
     #region Base class

src/mlnet/Templates/MLCodeGen.tt

@@ -100,10 +100,10 @@ else{#>
             // in order to evaluate and get the model's accuracy metrics
             Console.WriteLine("=============== Cross-validating to get model's accuracy metrics ===============");
 <#if("BinaryClassification".Equals(TaskType)){ #>
-            var crossValidationResults = mlContext.<#= TaskType #>.CrossValidateNonCalibrated(trainingDataView, trainingPipeline, numFolds: 3, labelColumn:"Label");
+            var crossValidationResults = mlContext.<#= TaskType #>.CrossValidateNonCalibrated(trainingDataView, trainingPipeline, numFolds: <#= Kfolds #>, labelColumn:"Label");
             ConsoleHelper.PrintBinaryClassificationFoldsAverageMetrics(trainer.ToString(), crossValidationResults);
 <#}#><#if("Regression".Equals(TaskType)){ #>
-            var crossValidationResults = mlContext.<#= TaskType #>.CrossValidate(trainingDataView, trainingPipeline, numFolds: 3, labelColumn:"Label");
+            var crossValidationResults = mlContext.<#= TaskType #>.CrossValidate(trainingDataView, trainingPipeline, numFolds: <#= Kfolds #>, labelColumn:"Label");
             ConsoleHelper.PrintRegressionFoldsAverageMetrics(trainer.ToString(), crossValidationResults);
 <#}#>
 <# } #>
@@ -205,4 +205,5 @@ public string GeneratedUsings {get;set;}
 public bool AllowQuoting {get;set;}
 public bool AllowSparse {get;set;}
 public bool TrimWhiteSpace {get;set;} 
+public int Kfolds {get;set;} = 5;
 #>