Tune model parameters

src/main/java/com/naaturel/ANN/Main.java

@@ -33,11 +33,10 @@ public class Main {
         float learningRate = config.getTrainingProperty("learning_rate", Double.class).floatValue();
         String datasetPath = config.getDatasetProperty("path", String.class);
 
-        int nbrClass = 1;
+        int nbrClass = 5;
         DataSet dataset = new DatasetExtractor().extract(datasetPath, nbrClass);
         int nbrInput = dataset.getNbrInputs();
 
-
         ModelSnapshot snapshot;
 
         Model network;
@@ -47,14 +46,13 @@ public class Main {
             System.out.println("Parameters: " + network.synCount());
             Trainer trainer = new GradientBackpropagationTraining();
             trainer.train(learningRate, maxEpoch, network, dataset);
+            snapshot.saveToFile(modelPath);
         } else {
             snapshot = new ModelSnapshot();
             snapshot.loadFromFile(modelPath);
             network = snapshot.getModel();
         }
-
-        plotGraph(dataset, network);
-        snapshot.saveToFile(modelPath);
+        //plotGraph(dataset, network);
     }
 
     private static FullyConnectedNetwork createNetwork(int[] neuronPerLayer, int nbrInput){
@@ -96,8 +94,8 @@ public class Main {
             });
         }
 
-        float min = -0F;
-        float max = 10F;
+        float min = -5F;
+        float max = 5F;
         float step = 0.03F;
         for (float x = min; x < max; x+=step){
             for (float y = min; y < max; y+=step){