Revised the classification ML model

Added MLModel2

TicTacToeML/MLModel2.consumption.cs

@@ -0,0 +1,91 @@
+// This file was auto-generated by ML.NET Model Builder. 
+using Microsoft.ML;
+using Microsoft.ML.Data;
+using System;
+using System.Linq;
+using System.IO;
+using System.Collections.Generic;
+namespace TicTacToeML
+{
+    public partial class MLModel2
+    {
+        /// <summary>
+        /// model input class for MLModel2.
+        /// </summary>
+        #region model input class
+        public class ModelInput
+        {
+            [ColumnName(@"MoveNumber")]
+            public float MoveNumber { get; set; }
+
+            [ColumnName(@"Cell0")]
+            public float Cell0 { get; set; }
+
+            [ColumnName(@"Cell1")]
+            public float Cell1 { get; set; }
+
+            [ColumnName(@"Cell2")]
+            public float Cell2 { get; set; }
+
+            [ColumnName(@"Cell3")]
+            public float Cell3 { get; set; }
+
+            [ColumnName(@"Cell4")]
+            public float Cell4 { get; set; }
+
+            [ColumnName(@"Cell5")]
+            public float Cell5 { get; set; }
+
+            [ColumnName(@"Cell6")]
+            public float Cell6 { get; set; }
+
+            [ColumnName(@"Cell7")]
+            public float Cell7 { get; set; }
+
+            [ColumnName(@"Cell8")]
+            public float Cell8 { get; set; }
+
+            [ColumnName(@"GameResultCode")]
+            public float GameResultCode { get; set; }
+
+        }
+
+        #endregion
+
+        /// <summary>
+        /// model output class for MLModel2.
+        /// </summary>
+        #region model output class
+        public class ModelOutput
+        {
+            [ColumnName("PredictedLabel")]
+            public float Prediction { get; set; }
+
+            public float[] Score { get; set; }
+        }
+
+        #endregion
+
+        private static string MLNetModelPath = Path.GetFullPath("MLModel2.zip");
+
+        public static readonly Lazy<PredictionEngine<ModelInput, ModelOutput>> PredictEngine = new Lazy<PredictionEngine<ModelInput, ModelOutput>>(() => CreatePredictEngine(), true);
+
+        /// <summary>
+        /// Use this method to predict on <see cref="ModelInput"/>.
+        /// </summary>
+        /// <param name="input">model input.</param>
+        /// <returns><seealso cref=" ModelOutput"/></returns>
+        public static ModelOutput Predict(ModelInput input)
+        {
+            var predEngine = PredictEngine.Value;
+            return predEngine.Predict(input);
+        }
+
+        private static PredictionEngine<ModelInput, ModelOutput> CreatePredictEngine()
+        {
+            var mlContext = new MLContext();
+            ITransformer mlModel = mlContext.Model.Load(MLNetModelPath, out var _);
+            return mlContext.Model.CreatePredictionEngine<ModelInput, ModelOutput>(mlModel);
+        }
+    }
+}