diff --git a/testML/Program.cs b/testML/Program.cs
index d7b3c1b..4207f9e 100644
--- a/testML/Program.cs
+++ b/testML/Program.cs
@@ -18,34 +18,36 @@ namespace testML
 
 		static void Main(string[] args)
 		{
-			
-			
+
+			#region Preparamos los datos de entrenamiento
 
 			var tmpData = new List<Data>();
 		
-
-			for (var c = 0; c < 1000; c++)
+			for (var c = 0; c < 15000; c++)
 			{
 				var d = CreateRandomData();
 				tmpData.Add(d);
 			}
 
-			
+			#endregion
+
 
 			MLContext mlContext = new MLContext();
-
 			var data = mlContext.Data.LoadFromEnumerable(tmpData);
 
+			#region Cortamos los datos de entrenamiento en (Datos para entenar y Datos para hacer el test de precisión)
 
-			DataOperationsCatalog.TrainTestData dataSplit = mlContext.Data.TrainTestSplit(data, testFraction: 0.2);
+			DataOperationsCatalog.TrainTestData dataSplit = mlContext.Data.TrainTestSplit(data, testFraction: 0.1);
 			IDataView trainData = dataSplit.TrainSet;
 			IDataView testData = dataSplit.TestSet;
 
-			
+			#endregion
+
+			#region Preparamos los datos de entrada y salida
+
 			var trainer = mlContext.Regression.Trainers.Sdca(maximumNumberOfIterations:1000);
 			//var trainer = mlContext.Regression.Trainers.OnlineGradientDescent(numberOfIterations: 100, learningRate: 0.01f );
 
-
 			var pipeline = mlContext.Transforms.CopyColumns(outputColumnName: "Label", inputColumnName: "IntegerNumber")
 				.Append(mlContext.Transforms.Text.NormalizeText("StringTest"))
 				.Append(mlContext.Transforms.Text.FeaturizeText("StringTest"))
@@ -53,10 +55,12 @@ namespace testML
 				.Append(mlContext.Transforms.NormalizeMinMax("Features"))
 				.Append(trainer);
 
+			#endregion
 
-			
+			//Entrenamos el modelo
 			ITransformer model = pipeline.Fit(trainData);
-			
+
+			#region Hacemos un test para medir el % de error
 
 			// Use trained model to make inferences on test data
 			IDataView testDataPredictions = model.Transform(testData);
@@ -67,14 +71,15 @@ namespace testML
 
 			Console.WriteLine("ModelMetrics: {0}", rSquared);
 
+			#endregion
 
 
+			#region Ponemos a prueba haciendo algunas predicciones
+
 			var predictionFunction = mlContext.Model.CreatePredictionEngine<Data, DataPrediction>(model);
 
-
-			for (var c = 0; c < 1000; c++)
+			for (var c = 0; c < 25; c++)
 			{
-
 				var test = CreateRandomData();
 				var expected = test.IntegerNumber;
 				test.IntegerNumber = 0;
@@ -84,6 +89,13 @@ namespace testML
 				Console.WriteLine("Found: {0:#,##0.00}\tExpected: {1:#,##0.00}\t\tDiff: {2:#,##0.00}", p.IntegerNumber, expected , expected- p.IntegerNumber);
 			}
 
+			#endregion
+
+
+			Console.WriteLine();
+			Console.WriteLine("Press enter to Exit");
+			Console.ReadLine();
+
 		}
 
 		private static Data CreateRandomData()