Move dataset components

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

@@ -2,11 +2,10 @@ package com.naaturel.ANN;
 
 import com.naaturel.ANN.domain.model.neuron.Neuron;
 import com.naaturel.ANN.domain.abstraction.Trainer;
-import com.naaturel.ANN.domain.model.dataset.DataSet;
+import com.naaturel.ANN.infrastructure.dataset.DataSet;
-import com.naaturel.ANN.domain.model.dataset.DatasetExtractor;
+import com.naaturel.ANN.infrastructure.dataset.DatasetExtractor;
 import com.naaturel.ANN.domain.model.neuron.*;
 import com.naaturel.ANN.implementation.gradientDescent.Linear;
-import com.naaturel.ANN.implementation.training.AdalineTraining;
 import com.naaturel.ANN.implementation.training.GradientDescentTraining;
 
 import java.util.*;
@@ -18,25 +17,31 @@ public class Main {
         int nbrInput = 2;
         int nbrClass = 3;
 
+        int nbrLayers = 1;
+
         DataSet dataset = new DatasetExtractor()
                 .extract("C:/Users/Laurent/Desktop/ANN-framework/src/main/resources/assets/table_3_1.csv", nbrClass);
 
-        List<Neuron> neurons = new ArrayList<>();
+        List<Layer> layers = new ArrayList<>();
+        for(int i = 0; i < nbrLayers; i++){
 
-        for (int i=0; i < nbrClass; i++){
+            List<Neuron> neurons = new ArrayList<>();
-            List<Synapse> syns = new ArrayList<>();
+            for (int j=0; j < nbrClass; j++){
-            for (int j=0; j < nbrInput; j++){
+
-                syns.add(new Synapse(new Input(0), new Weight(0)));
+                List<Synapse> syns = new ArrayList<>();
+                for (int k=0; k < nbrInput; k++){
+                    syns.add(new Synapse(new Input(0), new Weight(0)));
+                }
+
+                Bias bias =  new Bias(new Weight(0));
+
+                Neuron n = new Neuron(syns, bias, new Linear());
+                neurons.add(n);
             }
-
+            Layer layer = new Layer(neurons);
-            Bias bias =  new Bias(new Weight(0));
+            layers.add(layer);
-
-            Neuron n = new Neuron(syns, bias, new Linear());
-            neurons.add(n);
         }
-
+        Network network = new Network(layers);
-        Layer layer = new Layer(neurons);
-        Network network = new Network(List.of(layer));
 
         Trainer trainer = new GradientDescentTraining();
         trainer.train(network, dataset);

src/main/java/com/naaturel/ANN/domain/abstraction/Trainer.java

@@ -1,6 +1,6 @@
 package com.naaturel.ANN.domain.abstraction;
 
-import com.naaturel.ANN.domain.model.dataset.DataSet;
+import com.naaturel.ANN.infrastructure.dataset.DataSet;
 
 public interface Trainer {
     void train(Model model, DataSet dataset);

src/main/java/com/naaturel/ANN/domain/abstraction/TrainingContext.java

@@ -1,7 +1,7 @@
 package com.naaturel.ANN.domain.abstraction;
 
-import com.naaturel.ANN.domain.model.dataset.DataSet;
+import com.naaturel.ANN.infrastructure.dataset.DataSet;
-import com.naaturel.ANN.domain.model.dataset.DataSetEntry;
+import com.naaturel.ANN.infrastructure.dataset.DataSetEntry;
 
 import java.util.List;
 

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

@@ -16,12 +16,11 @@ public class Network implements Model {
 
     @Override
     public List<Float> predict(List<Input> inputs) {
-        List<Float> result = new ArrayList<>();
+        List<Input> currentLayerOutput = new ArrayList<>(inputs);
         for(Layer layer : this.layers){
-            List<Float> res = layer.predict(inputs);
+            currentLayerOutput = layer.predict(currentLayerOutput).stream().map(Input::new).toList();
-            result.addAll(res);
         }
-        return result;
+        return currentLayerOutput.stream().map(Input::getValue).toList();
     }
 
     @Override

src/main/java/com/naaturel/ANN/domain/model/training/TrainingPipeline.java

@@ -2,7 +2,7 @@ package com.naaturel.ANN.domain.model.training;
 
 import com.naaturel.ANN.domain.abstraction.TrainingContext;
 import com.naaturel.ANN.domain.abstraction.TrainingStep;
-import com.naaturel.ANN.domain.model.dataset.DataSetEntry;
+import com.naaturel.ANN.infrastructure.dataset.DataSetEntry;
 import com.naaturel.ANN.domain.model.neuron.Input;
 import com.naaturel.ANN.infrastructure.graph.GraphVisualizer;
 

src/main/java/com/naaturel/ANN/implementation/simplePerceptron/SimpleDeltaStrategy.java

@@ -2,10 +2,9 @@ package com.naaturel.ANN.implementation.simplePerceptron;
 
 import com.naaturel.ANN.domain.abstraction.AlgorithmStrategy;
 import com.naaturel.ANN.domain.abstraction.TrainingContext;
-import com.naaturel.ANN.domain.model.dataset.DataSet;
+import com.naaturel.ANN.infrastructure.dataset.DataSet;
-import com.naaturel.ANN.domain.model.dataset.DataSetEntry;
+import com.naaturel.ANN.infrastructure.dataset.DataSetEntry;
 
-import java.util.ArrayList;
 import java.util.List;
 import java.util.stream.Collectors;
 import java.util.stream.IntStream;

src/main/java/com/naaturel/ANN/implementation/training/AdalineTraining.java

@@ -3,7 +3,7 @@ package com.naaturel.ANN.implementation.training;
 import com.naaturel.ANN.domain.abstraction.Model;
 import com.naaturel.ANN.domain.abstraction.Trainer;
 import com.naaturel.ANN.domain.abstraction.TrainingStep;
-import com.naaturel.ANN.domain.model.dataset.DataSet;
+import com.naaturel.ANN.infrastructure.dataset.DataSet;
 import com.naaturel.ANN.domain.model.training.TrainingPipeline;
 import com.naaturel.ANN.implementation.adaline.AdalineTrainingContext;
 import com.naaturel.ANN.implementation.gradientDescent.SquareLossStrategy;

src/main/java/com/naaturel/ANN/implementation/training/GradientDescentTraining.java

@@ -3,7 +3,7 @@ package com.naaturel.ANN.implementation.training;
 import com.naaturel.ANN.domain.abstraction.Model;
 import com.naaturel.ANN.domain.abstraction.Trainer;
 import com.naaturel.ANN.domain.abstraction.TrainingStep;
-import com.naaturel.ANN.domain.model.dataset.DataSet;
+import com.naaturel.ANN.infrastructure.dataset.DataSet;
 import com.naaturel.ANN.implementation.gradientDescent.GradientDescentErrorStrategy;
 import com.naaturel.ANN.implementation.gradientDescent.GradientDescentTrainingContext;
 import com.naaturel.ANN.domain.model.training.TrainingPipeline;
@@ -28,7 +28,7 @@ public class GradientDescentTraining implements Trainer {
         GradientDescentTrainingContext context = new GradientDescentTrainingContext();
         context.dataset = dataset;
         context.model = model;
-        context.learningRate = 0.0005F;
+        context.learningRate = 0.0008F;
         context.correctorTerms =  new ArrayList<>();
 
         List<TrainingStep> steps = List.of(
@@ -39,7 +39,7 @@ public class GradientDescentTraining implements Trainer {
         );
 
         new TrainingPipeline(steps)
-            .stopCondition(ctx -> ctx.globalLoss <= 0.00F || ctx.epoch > 50000)
+            .stopCondition(ctx -> ctx.globalLoss <= 0.08F || ctx.epoch > 150)
             .beforeEpoch(ctx -> {
                 GradientDescentTrainingContext gdCtx = (GradientDescentTrainingContext) ctx;
                 gdCtx.globalLoss = 0.0F;
@@ -50,9 +50,9 @@ public class GradientDescentTraining implements Trainer {
                 context.globalLoss /= context.dataset.size();
                 new GradientDescentCorrectionStrategy(context).apply();
             })
-            //.withVerbose(true)
+            .withVerbose(true)
             .withTimeMeasurement(true)
-            .withVisualization(false, new GraphVisualizer())
+            .withVisualization(true, new GraphVisualizer())
             .run(context);
     }
 

src/main/java/com/naaturel/ANN/implementation/training/SimpleTraining.java

@@ -3,7 +3,7 @@ package com.naaturel.ANN.implementation.training;
 import com.naaturel.ANN.domain.abstraction.Model;
 import com.naaturel.ANN.domain.abstraction.Trainer;
 import com.naaturel.ANN.domain.abstraction.TrainingStep;
-import com.naaturel.ANN.domain.model.dataset.DataSet;
+import com.naaturel.ANN.infrastructure.dataset.DataSet;
 import com.naaturel.ANN.implementation.simplePerceptron.*;
 import com.naaturel.ANN.domain.model.training.TrainingPipeline;
 import com.naaturel.ANN.implementation.training.steps.*;

src/main/java/com/naaturel/ANN/infrastructure/dataset/DataSet.java

@@ -1,4 +1,4 @@
-package com.naaturel.ANN.domain.model.dataset;
+package com.naaturel.ANN.infrastructure.dataset;
 
 import com.naaturel.ANN.domain.model.neuron.Input;
 

src/main/java/com/naaturel/ANN/infrastructure/dataset/DataSetEntry.java

@@ -1,4 +1,4 @@
-package com.naaturel.ANN.domain.model.dataset;
+package com.naaturel.ANN.infrastructure.dataset;
 
 import com.naaturel.ANN.domain.model.neuron.Input;
 

src/main/java/com/naaturel/ANN/infrastructure/dataset/DatasetExtractor.java

@@ -1,4 +1,4 @@
-package com.naaturel.ANN.domain.model.dataset;
+package com.naaturel.ANN.infrastructure.dataset;
 
 import com.naaturel.ANN.domain.model.neuron.Input;
 

src/main/java/com/naaturel/ANN/infrastructure/dataset/Labels.java

@@ -1,4 +1,4 @@
-package com.naaturel.ANN.domain.model.dataset;
+package com.naaturel.ANN.infrastructure.dataset;
 
 import java.util.List;
 

src/test/java/adaline/AdalineTest.java

@@ -3,8 +3,8 @@ package adaline;
 
 import com.naaturel.ANN.domain.model.neuron.Neuron;
 import com.naaturel.ANN.domain.abstraction.TrainingStep;
-import com.naaturel.ANN.domain.model.dataset.DataSet;
+import com.naaturel.ANN.infrastructure.dataset.DataSet;
-import com.naaturel.ANN.domain.model.dataset.DatasetExtractor;
+import com.naaturel.ANN.infrastructure.dataset.DatasetExtractor;
 import com.naaturel.ANN.domain.model.neuron.*;
 import com.naaturel.ANN.domain.model.training.TrainingPipeline;
 import com.naaturel.ANN.implementation.adaline.AdalineTrainingContext;

src/test/java/gradientDescent/GradientDescentTest.java

@@ -2,8 +2,8 @@ package gradientDescent;
 
 import com.naaturel.ANN.domain.model.neuron.Neuron;
 import com.naaturel.ANN.domain.abstraction.TrainingStep;
-import com.naaturel.ANN.domain.model.dataset.DataSet;
+import com.naaturel.ANN.infrastructure.dataset.DataSet;
-import com.naaturel.ANN.domain.model.dataset.DatasetExtractor;
+import com.naaturel.ANN.infrastructure.dataset.DatasetExtractor;
 import com.naaturel.ANN.domain.model.neuron.*;
 import com.naaturel.ANN.domain.model.training.TrainingPipeline;
 import com.naaturel.ANN.implementation.gradientDescent.*;

src/test/java/perceptron/SimplePerceptronTest.java

@@ -2,8 +2,8 @@ package perceptron;
 
 import com.naaturel.ANN.domain.model.neuron.Neuron;
 import com.naaturel.ANN.domain.abstraction.TrainingStep;
-import com.naaturel.ANN.domain.model.dataset.DataSet;
+import com.naaturel.ANN.infrastructure.dataset.DataSet;
-import com.naaturel.ANN.domain.model.dataset.DatasetExtractor;
+import com.naaturel.ANN.infrastructure.dataset.DatasetExtractor;
 import com.naaturel.ANN.domain.model.neuron.*;
 import com.naaturel.ANN.domain.model.training.TrainingPipeline;
 import com.naaturel.ANN.implementation.simplePerceptron.*;