[Src] Fixed typo: files in Microsoft.ML namespace

src/Microsoft.ML/Models/BinaryClassificationEvaluator.cs

@@ -18,7 +18,7 @@ public sealed partial class BinaryClassificationEvaluator
         /// The trained PredictionModel to be evaluated.
         /// </param>
         /// <param name="testData">
-        /// The test data that will be predicted and used to evaulate the model.
+        /// The test data that will be predicted and used to evaluate the model.
         /// </param>
         /// <returns>
         /// A BinaryClassificationMetrics instance that describes how well the model performed against the test data.

src/Microsoft.ML/Models/ClassificationEvaluator.cs

@@ -18,7 +18,7 @@ public sealed partial class ClassificationEvaluator
         /// The trained multi-class classification PredictionModel to be evaluated.
         /// </param>
         /// <param name="testData">
-        /// The test data that will be predicted and used to evaulate the model.
+        /// The test data that will be predicted and used to evaluate the model.
         /// </param>
         /// <returns>
         /// A ClassificationMetrics instance that describes how well the model performed against the test data.

src/Microsoft.ML/Models/RegressionEvaluator.cs

@@ -18,7 +18,7 @@ public sealed partial class RegressionEvaluator
         /// The trained PredictionModel to be evaluated.
         /// </param>
         /// <param name="testData">
-        /// The test data that will be predicted and used to evaulate the model.
+        /// The test data that will be predicted and used to evaluate the model.
         /// </param>
         /// <returns>
         /// A RegressionMetrics instance that describes how well the model performed against the test data.

src/Microsoft.ML/Runtime/EntryPoints/CodeGen/TransformGenerators.cs

@@ -200,7 +200,7 @@ protected override void GenerateContent(IndentingTextWriter writer, string prefi
         {
             writer.WriteLine("[Module(");
             _compName = prefix + component.LoadNames[0];
-            var name = Name ?? PrettyPrintDiaplayName(component.LoadNames[0]);
+            var name = Name ?? PrettyPrintDisplayName(component.LoadNames[0]);
             using (writer.Nest())
             {
                 writer.WriteLine("Name = \"{0}\",", name);
@@ -460,15 +460,15 @@ protected override void GenerateParameter(IndentingTextWriter w, string type, st
         private void GenerateParameterAttribute(IndentingTextWriter w, string displayName, object defaultValue, string description,
             string parent = null, string parentType = null, string parentValue = null)
         {
-            w.WriteLine("[Help(Display = @\"{0}\", ToolTip = \"{1}\")]", PrettyPrintDiaplayName(displayName), description);
+            w.WriteLine("[Help(Display = @\"{0}\", ToolTip = \"{1}\")]", PrettyPrintDisplayName(displayName), description);
             if (parent != null)
                 w.WriteLine("[Relevancy(Key = \"{0}\", Values = new object[] {{ {1}.{2} }})]", parent, parentType, parentValue);
             if (defaultValue != null)
                 w.WriteLine("[Domain(DefaultValue = {0})]", defaultValue);
             w.WriteLine("[ModuleParameter]");
         }
 
-        private string PrettyPrintDiaplayName(string displayName)
+        private string PrettyPrintDisplayName(string displayName)
         {
             var sb = new StringBuilder();
             bool first = true;

src/Microsoft.ML/Runtime/EntryPoints/CrossValidationBinaryMacro.cs

@@ -37,7 +37,7 @@ public sealed class SubGraphOutput
 
         public sealed class Arguments
         {
-            // This is the data used in the cross validataion. It will be split into k folds
+            // This is the data used in the cross validation. It will be split into k folds
             // and a model will be trained and evaluated for each fold.
             [TlcModule.OptionalInput]
             [Argument(ArgumentType.Required, HelpText = "The data set", SortOrder = 1)]

src/Microsoft.ML/Runtime/EntryPoints/CrossValidationMacro.cs

@@ -35,7 +35,7 @@ public sealed class SubGraphOutput
 
         public sealed class Arguments
         {
-            // This is the data used in the cross validataion. It will be split into k folds
+            // This is the data used in the cross validation. It will be split into k folds
             // and a model will be trained and evaluated for each fold.
             [TlcModule.OptionalInput]
             [Argument(ArgumentType.Required, HelpText = "The data set", SortOrder = 1)]