Minor changes

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

@@ -26,7 +26,7 @@ public class Main {
         DataSet dataset = new DatasetExtractor()
                 .extract("C:/Users/Laurent/Desktop/ANN-framework/src/main/resources/assets/table_4_12.csv", nbrClass);
 
-        int[] neuronPerLayer = new int[]{100, 100, 50, dataset.getNbrLabels()};
+        int[] neuronPerLayer = new int[]{50, 50, 25, dataset.getNbrLabels()};
         int nbrInput = dataset.getNbrInputs();
 
         FullyConnectedNetwork network = createNetwork(neuronPerLayer, nbrInput);
@@ -34,7 +34,7 @@ public class Main {
         System.out.println(network.synCount());
 
         Trainer trainer = new GradientBackpropagationTraining();
-        trainer.train(0.01F, 2000, network, dataset);
+        trainer.train(0.001F, 2000, network, dataset);
 
         //plotGraph(dataset, network);
     }

src/main/java/com/naaturel/ANN/domain/model/neuron/Neuron.java

@@ -46,7 +46,7 @@ public class Neuron implements Model {
     }
 
     public float calculateWeightedSum() {
-        int count = synCount();
+        int count = weights.length;
         float weightedSum = 0F;
         for (int i = 0; i < count; i++){
             weightedSum += weights[i] * inputs[i];