Naaturel/ANN-framework
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Reimplement Adaline

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Laurent
2026-03-26 11:27:10 +01:00
parent c389646794
commit 0d3ab0de8d
11 changed files with 187 additions and 25 deletions
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9
src/main/java/com/naaturel/ANN/Main.java
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@@ -8,6 +8,7 @@ import com.naaturel.ANN.domain.model.neuron.*;
import com.naaturel.ANN.implementation.gradientDescent.Linear;
import com.naaturel.ANN.implementation.simplePerceptron.Heaviside;
import com.naaturel.ANN.implementation.neuron.SimplePerceptron;
import com.naaturel.ANN.implementation.training.AdalineTraining;
import com.naaturel.ANN.implementation.training.GradientDescentTraining;
import com.naaturel.ANN.implementation.training.SimpleTraining;
@@ -21,7 +22,7 @@ public class Main {
.extract("C:/Users/Laurent/Desktop/ANN-framework/src/main/resources/assets/table_2_9.csv");
DataSet andDataset = new DatasetExtractor()
.extract("C:/Users/Laurent/Desktop/ANN-framework/src/main/resources/assets/and.csv");
.extract("C:/Users/Laurent/Desktop/ANN-framework/src/main/resources/assets/and-gradient.csv");
List<Synapse> syns = new ArrayList<>();
syns.add(new Synapse(new Input(0), new Weight(0)));
@@ -29,12 +30,12 @@ public class Main {
Bias bias = new Bias(new Weight(0));
Neuron neuron = new SimplePerceptron(syns, bias, new Heaviside());
Neuron neuron = new SimplePerceptron(syns, bias, new Linear());
Layer layer = new Layer(List.of(neuron));
Network network = new Network(List.of(layer));
Trainer trainer = new SimpleTraining();
trainer.train(network, andDataset);
Trainer trainer = new AdalineTraining();
trainer.train(network, dataset);
}
}