[Tiny & Simple Change] Example classes should be static

docs/samples/Microsoft.ML.Samples/Dynamic/Calibrator.cs

@@ -8,9 +8,9 @@ namespace Microsoft.ML.Samples.Dynamic
     /// <summary>
     /// This example first trains a StochasticDualCoordinateAscentBinary Classifier and then convert its output to probability via training a calibrator.  
     /// </summary>
-    public class CalibratorExample
+    public static class Calibrator
     {
-        public static void Calibration()
+        public static void Example()
         {
             // Downloading the dataset from github.com/dotnet/machinelearning.
             // This will create a sentiment.tsv file in the filesystem.

docs/samples/Microsoft.ML.Samples/Dynamic/DataOperations/BootstrapSample.cs

@@ -4,7 +4,7 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public static class BootstrapSample
+    public static class Bootstrap
     {
         public static void Example()
         {

docs/samples/Microsoft.ML.Samples/Dynamic/FastTreeRegression.cs

@@ -4,9 +4,9 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class FastTreeRegressionExample
+    public static class FastTreeRegression
     {
-        public static void FastTreeRegression()
+        public static void Example()
         {
             // Create a new ML context, for ML.NET operations. It can be used for exception tracking and logging, 
             // as well as the source of randomness.

docs/samples/Microsoft.ML.Samples/Dynamic/FeatureContributionCalculationTransform.cs

@@ -4,7 +4,7 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class FeatureContributionCalculationTransform
+    public static class FeatureContributionCalculationTransform
     {
         public static void Example()
         {

docs/samples/Microsoft.ML.Samples/Dynamic/FeatureSelectionTransform.cs

@@ -4,9 +4,9 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class FeatureSelectionTransformExample
+    public static class FeatureSelectionTransform
     {
-        public static void FeatureSelectionTransform()
+        public static void Example()
         {
             // Downloading a classification dataset from github.com/dotnet/machinelearning.
             // It will be stored in the same path as the executable

docs/samples/Microsoft.ML.Samples/Dynamic/FieldAwareFactorizationMachine.cs

@@ -2,9 +2,9 @@
 using Microsoft.ML.Data;
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class FFM_BinaryClassificationExample
+    public static class FFMBinaryClassification
     {
-        public static void FFM_BinaryClassification()
+        public static void Example()
         {
             // Downloading the dataset from github.com/dotnet/machinelearning.
             // This will create a sentiment.tsv file in the filesystem.

docs/samples/Microsoft.ML.Samples/Dynamic/GeneralizedAdditiveModels.cs

@@ -4,9 +4,9 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class GeneralizedAdditiveModels_RegressionExample
+    public static class GeneralizedAdditiveModelsRegression
     {
-        public static void RunExample()
+        public static void Example()
         {
             // Create a new context for ML.NET operations. It can be used for exception tracking and logging, 
             // as a catalog of available operations and as the source of randomness.

docs/samples/Microsoft.ML.Samples/Dynamic/IidChangePointDetectorTransform.cs

@@ -10,7 +10,7 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public partial class TransformSamples
+    public static partial class TransformSamples
     {
         class ChangePointPrediction
         {

docs/samples/Microsoft.ML.Samples/Dynamic/IidSpikeDetectorTransform.cs

@@ -6,7 +6,7 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public partial class TransformSamples
+    public static partial class TransformSamples
     {
         class IidSpikeData
         {

docs/samples/Microsoft.ML.Samples/Dynamic/ImageAnalytics/ConvertToGrayScale.cs

@@ -3,10 +3,10 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class ConvertToGrayscaleExample
+    public static class ConvertToGrayscale
     {
         // Sample that loads images from the file system, and converts them to grayscale. 
-        public static void ConvertToGrayscale()
+        public static void Example()
         {
             var mlContext = new MLContext();
 

docs/samples/Microsoft.ML.Samples/Dynamic/ImageAnalytics/ExtractPixels.cs

@@ -3,11 +3,11 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class ExtractPixelsExample
+    public static class ExtractPixels
     {
         // Sample that loads the images from the file system, resizes them (ExtractPixels requires a resizing operation), and extracts the 
         // values of the pixels as a vector. 
-        public static void ExtractPixels()
+        public static void Example()
         {
             var mlContext = new MLContext();
 

docs/samples/Microsoft.ML.Samples/Dynamic/ImageAnalytics/LoadImage.cs

@@ -3,10 +3,10 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class LoadImageExample
+    public static class LoadImage
     {
         // Loads the images of the imagesFolder into an IDataView. 
-        public static void LoadImage()
+        public static void Example()
         {
             var mlContext = new MLContext();
 

docs/samples/Microsoft.ML.Samples/Dynamic/ImageAnalytics/ResizeImage.cs

@@ -3,10 +3,10 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class ResizeImageExample
+    public static class ResizeImage
     {
         // Example on how to load the images from the file system, and resize them. 
-        public static void ResizeImage()
+        public static void Example()
         {
             var mlContext = new MLContext();
 

docs/samples/Microsoft.ML.Samples/Dynamic/KMeans.cs

@@ -3,9 +3,9 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class KMeans_example
+    public class KMeans
     {
-        public static void KMeans()
+        public static void Example()
         {
             // Create a new ML context, for ML.NET operations. It can be used for exception tracking and logging, 
             // as well as the source of randomness.

docs/samples/Microsoft.ML.Samples/Dynamic/KeyToValueValueToKey.cs

@@ -2,13 +2,12 @@
 using System.Collections.Generic;
 using Microsoft.ML.Data;
 using Microsoft.ML.Transforms.Conversions;
-using Microsoft.ML.Transforms.Text;
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class KeyToValueValueToKeyExample
+    public class KeyToValueValueToKey
     {
-        public static void KeyToValueValueToKey()
+        public static void Example()
         {
             // Create a new ML context, for ML.NET operations. It can be used for exception tracking and logging, 
             // as well as the source of randomness.

docs/samples/Microsoft.ML.Samples/Dynamic/LdaTransform.cs

@@ -4,9 +4,9 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class LdaTransformExample
+    public static class LdaTransform
     {
-        public static void LdaTransform()
+        public static void Example()
         {
             // Create a new ML context, for ML.NET operations. It can be used for exception tracking and logging, 
             // as well as the source of randomness.

docs/samples/Microsoft.ML.Samples/Dynamic/LogisticRegression.cs

@@ -4,9 +4,9 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class LogisticRegressionExample
+    public static class LogisticRegressionExample
     {
-        public static void LogisticRegression()
+        public static void Example()
         {
             var ml = new MLContext();
 

docs/samples/Microsoft.ML.Samples/Dynamic/NgramExtraction.cs

@@ -4,7 +4,7 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public partial class NgramTransformSamples
+    public static partial class TransformSamples
     {
         public static void NgramTransform()
         {

docs/samples/Microsoft.ML.Samples/Dynamic/Normalizer.cs

@@ -6,9 +6,9 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class NormalizerExample
+    public static class NormalizerTransform
     {
-        public static void Normalizer()
+        public static void Example()
         {
             // Create a new ML context, for ML.NET operations. It can be used for exception tracking and logging, 
             // as well as the source of randomness.

docs/samples/Microsoft.ML.Samples/Dynamic/OnnxTransform.cs

@@ -6,12 +6,12 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    class OnnxTransformExample
+    public static class OnnxTransformExample
     {
         /// <summary>
         /// Example use of OnnxEstimator in an ML.NET pipeline
         /// </summary>
-        public static void OnnxTransformSample()
+        public static void Example()
         {
             // Download the squeeznet image model from ONNX model zoo, version 1.2
             // https://github.com/onnx/models/tree/master/squeezenet

docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PFIHelper.cs

@@ -1,14 +1,13 @@
 using System;
 using System.Linq;
 using Microsoft.Data.DataView;
-using Microsoft.ML.Data;
 using Microsoft.ML.Trainers;
 using Microsoft.ML.SamplesUtils;
 using Microsoft.ML.Trainers.HalLearners;
 
 namespace Microsoft.ML.Samples.Dynamic.PermutationFeatureImportance
 {
-    public class PfiHelper
+    public static class PfiHelper
     {
         public static IDataView GetHousingRegressionIDataView(MLContext mlContext, out string labelName, out string[] featureNames, bool binaryPrediction = false)
         {

docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PFIRegressionExample.cs

@@ -3,9 +3,9 @@
 
 namespace Microsoft.ML.Samples.Dynamic.PermutationFeatureImportance
 {
-    public class PfiRegressionExample
+    public static class PfiRegression
     {
-        public static void RunExample()
+        public static void Example()
         {
             // Create a new context for ML.NET operations. It can be used for exception tracking and logging, 
             // as a catalog of available operations and as the source of randomness.

docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PfiBinaryClassificationExample.cs

@@ -4,9 +4,9 @@
 
 namespace Microsoft.ML.Samples.Dynamic.PermutationFeatureImportance
 {
-    public class PfiBinaryClassificationExample
+    public static class PfiBinaryClassification
     {
-        public static void RunExample()
+        public static void Example()
         {
             // Create a new context for ML.NET operations. It can be used for exception tracking and logging, 
             // as a catalog of available operations and as the source of randomness.

docs/samples/Microsoft.ML.Samples/Dynamic/ProjectionTransforms.cs

@@ -5,9 +5,9 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class ProjectionTransformsExample
+    public static class ProjectionTransforms
     {
-        public static void ProjectionTransforms()
+        public static void Example()
         {
             // Create a new ML context, for ML.NET operations. It can be used for exception tracking and logging, 
             // as well as the source of randomness.

docs/samples/Microsoft.ML.Samples/Dynamic/SDCARegression.cs

@@ -4,9 +4,9 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class SDCARegressionExample
+    public static class SDCARegression
     {
-        public static void SDCARegression()
+        public static void Example()
         {
             // Create a new ML context, for ML.NET operations. It can be used for exception tracking and logging, 
             // as well as the source of randomness.

docs/samples/Microsoft.ML.Samples/Dynamic/SsaChangePointDetectorTransform.cs

@@ -6,7 +6,7 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public partial class TransformSamples
+    public static partial class TransformSamples
     {
         class SsaChangePointData
         {

docs/samples/Microsoft.ML.Samples/Dynamic/SsaSpikeDetectorTransform.cs

@@ -6,7 +6,7 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public partial class TransformSamples
+    public static partial class TransformSamples
     {
         class SsaSpikeData
         {

docs/samples/Microsoft.ML.Samples/Dynamic/StopWordRemoverTransform.cs

@@ -5,9 +5,9 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class StopWordRemoverTransformExample
+    public static class StopWordRemoverTransform
     {
-        public static void StopWordRemoverTransform()
+        public static void Example()
         {
             // Create a new ML context, for ML.NET operations. It can be used for exception tracking and logging, 
             // as well as the source of randomness.

docs/samples/Microsoft.ML.Samples/Dynamic/TensorFlow/ImageClassification.cs

@@ -4,12 +4,12 @@
 
 namespace Microsoft.ML.Samples.Dynamic.TensorFlow
 {
-    class ImageClassification
+    public static class ImageClassification
     {
         /// <summary>
         /// Example use of the TensorFlow image model in a ML.NET pipeline.
         /// </summary>
-        public static void ScoringWithImageClassificationModelSample()
+        public static void Example()
         {
             // Download the ResNet 101 model from the location below.
             // https://storage.googleapis.com/download.tensorflow.org/models/tflite_11_05_08/resnet_v2_101.tgz

docs/samples/Microsoft.ML.Samples/Dynamic/TensorFlow/TextClassification.cs

@@ -1,18 +1,17 @@
 using System;
 using System.IO;
-using System.Linq;
 using Microsoft.ML.Data;
 using Microsoft.ML.Transforms.TensorFlow;
 
 namespace Microsoft.ML.Samples.Dynamic.TensorFlow
 {
-    class TextClassification
+    public static class TextClassification
     {
         public const int MaxSentenceLenth = 600;
         /// <summary>
         /// Example use of the TensorFlow sentiment classification model.
         /// </summary>
-        public static void ScoringWithTextClassificationModelSample()
+        public static void Example()
         {
             string modelLocation = SamplesUtils.DatasetUtils.DownloadTensorFlowSentimentModel();
 

docs/samples/Microsoft.ML.Samples/Dynamic/TextTransform.cs

@@ -5,9 +5,9 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class TextTransformExample
+    public static class TextTransform
     {
-        public static void TextTransform()
+        public static void Example()
         {
             // Create a new ML context, for ML.NET operations. It can be used for exception tracking and logging, 
             // as well as the source of randomness.

docs/samples/Microsoft.ML.Samples/Dynamic/Trainers/BinaryClassification/SDCALogisticRegression.cs

@@ -5,7 +5,7 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class SDCALogisticRegression
+    public static class SDCALogisticRegression
     {
         public static void Example()
         {

docs/samples/Microsoft.ML.Samples/Dynamic/Trainers/BinaryClassification/SDCASupportVectorMachine.cs

@@ -4,7 +4,7 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public class SDCASupportVectorMachine
+    public static class SDCASupportVectorMachine
     {
         public static void Example()
         {