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Move dataset components

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This commit is contained in:
Laurent
2026-03-28 12:25:59 +01:00
parent 7fb4a7c057
commit 6d88651385
16 changed files with 47 additions and 44 deletions
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21
src/main/java/com/naaturel/ANN/Main.java
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@@ -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.domain.model.dataset.DatasetExtractor;
import com.naaturel.ANN.infrastructure.dataset.DataSet;
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.*;
@@ -18,14 +17,19 @@ 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++){
List<Neuron> neurons = new ArrayList<>();
for (int j=0; j < nbrClass; j++){
for (int i=0; i < nbrClass; i++){
List<Synapse> syns = new ArrayList<>();
for (int j=0; j < nbrInput; j++){
for (int k=0; k < nbrInput; k++){
syns.add(new Synapse(new Input(0), new Weight(0)));
}
@@ -34,9 +38,10 @@ public class Main {
Neuron n = new Neuron(syns, bias, new Linear());
neurons.add(n);
}
Layer layer = new Layer(neurons);
Network network = new Network(List.of(layer));
layers.add(layer);
}
Network network = new Network(layers);
Trainer trainer = new GradientDescentTraining();
trainer.train(network, dataset);

2
src/main/java/com/naaturel/ANN/domain/abstraction/Trainer.java
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@@ -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);

4
src/main/java/com/naaturel/ANN/domain/abstraction/TrainingContext.java
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@@ -1,7 +1,7 @@
package com.naaturel.ANN.domain.abstraction;
import com.naaturel.ANN.domain.model.dataset.DataSet;
import com.naaturel.ANN.domain.model.dataset.DataSetEntry;
import com.naaturel.ANN.infrastructure.dataset.DataSet;
import com.naaturel.ANN.infrastructure.dataset.DataSetEntry;
import java.util.List;

7
src/main/java/com/naaturel/ANN/domain/model/neuron/Network.java
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@@ -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);
result.addAll(res);
currentLayerOutput = layer.predict(currentLayerOutput).stream().map(Input::new).toList();
}
return result;
return currentLayerOutput.stream().map(Input::getValue).toList();
}
@Override

2
src/main/java/com/naaturel/ANN/domain/model/training/TrainingPipeline.java
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@@ -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;

5
src/main/java/com/naaturel/ANN/implementation/simplePerceptron/SimpleDeltaStrategy.java
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@@ -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.domain.model.dataset.DataSetEntry;
import com.naaturel.ANN.infrastructure.dataset.DataSet;
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;

2
src/main/java/com/naaturel/ANN/implementation/training/AdalineTraining.java
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@@ -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;

10
src/main/java/com/naaturel/ANN/implementation/training/GradientDescentTraining.java
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@@ -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);
}

2
src/main/java/com/naaturel/ANN/implementation/training/SimpleTraining.java
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@@ -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.*;

2
src/main/java/com/naaturel/ANN/domain/model/dataset/DataSet.java → src/main/java/com/naaturel/ANN/infrastructure/dataset/DataSet.java
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@@ -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;

2
src/main/java/com/naaturel/ANN/domain/model/dataset/DataSetEntry.java → src/main/java/com/naaturel/ANN/infrastructure/dataset/DataSetEntry.java
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@@ -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;

2
src/main/java/com/naaturel/ANN/domain/model/dataset/DatasetExtractor.java → src/main/java/com/naaturel/ANN/infrastructure/dataset/DatasetExtractor.java
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@@ -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;

2
src/main/java/com/naaturel/ANN/domain/model/dataset/Labels.java → src/main/java/com/naaturel/ANN/infrastructure/dataset/Labels.java
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@@ -1,4 +1,4 @@
package com.naaturel.ANN.domain.model.dataset;
package com.naaturel.ANN.infrastructure.dataset;
import java.util.List;

4
src/test/java/adaline/AdalineTest.java
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@@ -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.domain.model.dataset.DatasetExtractor;
import com.naaturel.ANN.infrastructure.dataset.DataSet;
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;

4
src/test/java/gradientDescent/GradientDescentTest.java
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@@ -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.domain.model.dataset.DatasetExtractor;
import com.naaturel.ANN.infrastructure.dataset.DataSet;
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.*;

4
src/test/java/perceptron/SimplePerceptronTest.java
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@@ -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.domain.model.dataset.DatasetExtractor;
import com.naaturel.ANN.infrastructure.dataset.DataSet;
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.*;