diff --git a/testML/Program.cs b/testML/Program.cs
index 4207f9e..51e4841 100644
--- a/testML/Program.cs
+++ b/testML/Program.cs
@@ -23,7 +23,7 @@ namespace testML
 
 			var tmpData = new List<Data>();
 		
-			for (var c = 0; c < 15000; c++)
+			for (var c = 0; c < 100000; c++)
 			{
 				var d = CreateRandomData();
 				tmpData.Add(d);
@@ -49,9 +49,9 @@ namespace testML
 			//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"))
-				.Append(mlContext.Transforms.Concatenate("Features", "Enum1", "Enum2", "Enum3", "Enum4", "StringTest"))
+				//.Append(mlContext.Transforms.Text.NormalizeText("StringTest"))
+				//.Append(mlContext.Transforms.Text.FeaturizeText("StringTest"))
+				.Append(mlContext.Transforms.Concatenate("Features", "Enum1", "Enum2", "Enum3", "Enum4"))
 				.Append(mlContext.Transforms.NormalizeMinMax("Features"))
 				.Append(trainer);
 
@@ -78,15 +78,18 @@ namespace testML
 
 			var predictionFunction = mlContext.Model.CreatePredictionEngine<Data, DataPrediction>(model);
 
-			for (var c = 0; c < 25; c++)
+			for (var c = 0; c < 1000; c++)
 			{
 				var test = CreateRandomData();
 				var expected = test.IntegerNumber;
 				test.IntegerNumber = 0;
 
 				var p = predictionFunction.Predict(test);
-				
-				Console.WriteLine("Found: {0:#,##0.00}\tExpected: {1:#,##0.00}\t\tDiff: {2:#,##0.00}", p.IntegerNumber, expected , expected- p.IntegerNumber);
+
+				//p.IntegerNumber = (float)Math.Round(p.IntegerNumber);
+
+
+				Console.WriteLine("{4} {3}, Found: {0:#,##0.00}\tExpected: {1:#,##0.00}\t\tDiff: {2:#,##0.00}", p.IntegerNumber, expected , expected- p.IntegerNumber, test.Enum4, test.Enum2);
 			}
 
 			#endregion
@@ -106,26 +109,17 @@ namespace testML
 				Enum1 = rnd.Next(1, 4),
 				Enum2 = rnd.Next(1, 11),
 				Enum3 = rnd.Next(1, 6),
-				Enum4 = rnd.Next(1, 6),
+				Enum4 = rnd.Next(1, 4),
 				StringTest = tags[rnd.Next(0, tags.Length)]
 			};
 
-			// Ponemos algunos datos que tengan alguna relación (la red neuronal debería calibrarse para comprender esta formula)
-			d.IntegerNumber = (((d.Enum1 + d.Enum2) - (d.Enum3 + d.Enum4)) * 5.25f) + d.StringTest.Length;
-			
-			d.DecimalNumber = (d.Enum2 / d.Enum1) * (2.0f + (1.0f / d.StringTest.Length));
-
-			if (d.StringTest == "Azul")
+			switch (d.Enum4)
 			{
-				d.IntegerNumber += 10;
-				d.OrigenResultNumber = 1;
+				case 1: d.IntegerNumber = 1; break;
+				case 2: d.IntegerNumber = rnd.NextDouble() > 0.5 ? 1 : 0; break;
+				case 3: d.IntegerNumber = 0; break;
 			}
 
-			if (d.StringTest == "Rojo")
-			{
-				d.IntegerNumber += 5f;
-				d.OrigenResultNumber = 1;
-			}
 
 			return d;
 
diff --git a/testML/testML.csproj b/testML/testML.csproj
index b5a7157..874e1a7 100644
--- a/testML/testML.csproj
+++ b/testML/testML.csproj
@@ -18,7 +18,7 @@
     </NuGetPackageImportStamp>
   </PropertyGroup>
   <PropertyGroup Condition=" '$(Configuration)|$(Platform)' == 'Debug|AnyCPU' ">
-    <PlatformTarget>x64</PlatformTarget>
+    <PlatformTarget>x86</PlatformTarget>
     <DebugSymbols>true</DebugSymbols>
     <DebugType>full</DebugType>
     <Optimize>false</Optimize>