Revize cdeee9f8

Re #8955 implemented multiple predictors support

Server/ServerApp/Predictor/NaiveBayesClassifier.cs

@@ -40 +40 @@
         {
             this._trainingDataView = _mlContext.Data.LoadFromEnumerable(trainInput);
             var pipeline = _mlContext.Transforms.Conversion.MapValueToKey(nameof(ModelInput.Label))
-                .Append(_mlContext.Transforms.Concatenate("Features", new[] { nameof(ModelInput.Temp), nameof(ModelInput.Rain), nameof(ModelInput.Wind) }))
+                .Append(_mlContext.Transforms.Conversion.ConvertType(nameof(ModelInput.Hour)))
+                .Append(_mlContext.Transforms.Concatenate("Features", 
+                new[] { nameof(ModelInput.Temp), nameof(ModelInput.Rain), nameof(ModelInput.Wind), nameof(ModelInput.Hour) }))
                 .Append(_mlContext.Transforms.NormalizeMinMax("Features", "Features"))
                 .AppendCacheCheckpoint(_mlContext)
                 .Append(_mlContext.MulticlassClassification.Trainers.NaiveBayes())
                 .Append(_mlContext.Transforms.Conversion.MapKeyToValue(nameof(ModelOutput.PredictedLabel)));
 
-            this._trainedModel = pipeline.Fit(this._trainingDataView);
+            var cvResults = _mlContext.MulticlassClassification.CrossValidate(this._trainingDataView, pipeline);
+            foreach (var result in cvResults)
+            {
+                var testMetrics = result.Metrics;
+                Console.WriteLine($"*************************************************************************************************************");
+                Console.WriteLine($"*       Metrics for Multi-class Classification model - Model #{result.Fold}    ");
+                Console.WriteLine($"*------------------------------------------------------------------------------------------------------------");
+                Console.WriteLine($"*       MicroAccuracy:    {testMetrics.MicroAccuracy:0.###}");
+                Console.WriteLine($"*       MacroAccuracy:    {testMetrics.MacroAccuracy:0.###}");
+                Console.WriteLine($"*       LogLoss:          {testMetrics.LogLoss:#.###}");
+                Console.WriteLine($"*       LogLossReduction: {testMetrics.LogLossReduction:#.###}");
+                Console.WriteLine($"*       Confusion Matrix: {testMetrics.ConfusionMatrix.GetFormattedConfusionTable()}");
+                Console.WriteLine($"*************************************************************************************************************");
+            }
+            this._trainedModel = cvResults.OrderByDescending(fold => fold.Metrics.MicroAccuracy).Select(fold => fold.Model).First();
+            Console.WriteLine($"Selected the model #{cvResults.OrderByDescending(fold => fold.Metrics.MicroAccuracy).Select(fold => fold.Fold).First()} as the best.");
             this._predictionEngine = _mlContext.Model.CreatePredictionEngine<ModelInput, ModelOutput>(this._trainedModel);
 
         }
@@ -69 +86 @@
             Console.WriteLine($"*       MacroAccuracy:    {testMetrics.MacroAccuracy:0.###}");
             Console.WriteLine($"*       LogLoss:          {testMetrics.LogLoss:#.###}");
             Console.WriteLine($"*       LogLossReduction: {testMetrics.LogLossReduction:#.###}");
+            Console.WriteLine($"*       Confusion Matrix: {testMetrics.ConfusionMatrix.GetFormattedConfusionTable()}");
             Console.WriteLine($"*************************************************************************************************************");
         }
     }