Refactored Perceptron
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54cfe2dece
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@ -6,10 +6,12 @@ import java.util.List;
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public class Perceptron
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{
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private Vector weight;
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public void learn(List<Vector> positives, List<Vector> negatives)
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{
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var iterationCounter = 0;
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var weight = this.getInitializationVector(positives, negatives);
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this.weight = this.getInitializationVector(positives, negatives);
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do
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{
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@ -1,5 +1,6 @@
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package machine_learning.perceptron;
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import machine_learning.Vector;
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import org.junit.jupiter.api.BeforeAll;
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import org.junit.jupiter.api.Test;
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import org.junit.jupiter.api.TestInstance;
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@ -18,17 +19,17 @@ class PerceptronTest
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{
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double biasUnit = 1d;
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this.positives = new ArrayList<>(List.of(
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new Vector(List.of(8d, 4d, biasUnit)),
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new Vector(List.of(8d, 6d, biasUnit)),
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new Vector(List.of(9d, 2d, biasUnit)),
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new Vector(List.of(9d, 5d, biasUnit)))
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new Vector(8d, 4d, biasUnit),
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new Vector(8d, 6d, biasUnit),
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new Vector(9d, 2d, biasUnit),
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new Vector(9d, 5d, biasUnit))
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);
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this.negatives = new ArrayList<>(List.of(
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new Vector(List.of(6d, 1d, biasUnit)),
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new Vector(List.of(7d, 3d, biasUnit)),
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new Vector(List.of(8d, 2d, biasUnit)),
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new Vector(List.of(9d, 0d, biasUnit)))
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new Vector(6d, 1d, biasUnit),
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new Vector(7d, 3d, biasUnit),
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new Vector(8d, 2d, biasUnit),
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new Vector(9d, 0d, biasUnit))
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);
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}
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