BAEL-771 (#2286)

* BAEL-771

* Corrected XOR from mislabeled AND

* Unit tests added

* Merged into libraries module - removed Neuroph module

* Merged into libraries module - removed Neuroph module

* Merged pom.xml

* Merged pom.xml

* libraries pom.xml - I removed a white space during merge so conflict persisted - here's the temporary reversion

libraries/src/main/java/com/baeldung/neuroph/NeurophXOR.java

@@ -0,0 +1,73 @@
+package com.baeldung.neuroph;
+
+import org.neuroph.core.Layer;
+import org.neuroph.core.NeuralNetwork;
+import org.neuroph.core.Neuron;
+import org.neuroph.core.data.DataSet;
+import org.neuroph.core.data.DataSetRow;
+import org.neuroph.nnet.learning.BackPropagation;
+import org.neuroph.util.ConnectionFactory;
+import org.neuroph.util.NeuralNetworkType;
+
+public class NeurophXOR {
+
+    public static NeuralNetwork assembleNeuralNetwork() {
+
+        Layer inputLayer = new Layer();
+        inputLayer.addNeuron(new Neuron());
+        inputLayer.addNeuron(new Neuron());
+
+        Layer hiddenLayerOne = new Layer();
+        hiddenLayerOne.addNeuron(new Neuron());
+        hiddenLayerOne.addNeuron(new Neuron());
+        hiddenLayerOne.addNeuron(new Neuron());
+        hiddenLayerOne.addNeuron(new Neuron());
+
+        Layer hiddenLayerTwo = new Layer();
+        hiddenLayerTwo.addNeuron(new Neuron());
+        hiddenLayerTwo.addNeuron(new Neuron());
+        hiddenLayerTwo.addNeuron(new Neuron());
+        hiddenLayerTwo.addNeuron(new Neuron());
+
+        Layer outputLayer = new Layer();
+        outputLayer.addNeuron(new Neuron());
+
+        NeuralNetwork ann = new NeuralNetwork();
+
+        ann.addLayer(0, inputLayer);
+        ann.addLayer(1, hiddenLayerOne);
+        ConnectionFactory.fullConnect(ann.getLayerAt(0), ann.getLayerAt(1));
+        ann.addLayer(2, hiddenLayerTwo);
+        ConnectionFactory.fullConnect(ann.getLayerAt(1), ann.getLayerAt(2));
+        ann.addLayer(3, outputLayer);
+        ConnectionFactory.fullConnect(ann.getLayerAt(2), ann.getLayerAt(3));
+        ConnectionFactory.fullConnect(ann.getLayerAt(0), ann.getLayerAt(ann.getLayersCount()-1), false);
+
+        ann.setInputNeurons(inputLayer.getNeurons());
+        ann.setOutputNeurons(outputLayer.getNeurons());
+
+        ann.setNetworkType(NeuralNetworkType.MULTI_LAYER_PERCEPTRON);
+        return ann;
+    }
+
+    public static NeuralNetwork trainNeuralNetwork(NeuralNetwork ann) {
+        int inputSize = 2;
+        int outputSize = 1;
+        DataSet ds = new DataSet(inputSize, outputSize);
+
+        DataSetRow rOne = new DataSetRow(new double[] {0, 1}, new double[] {1});
+        ds.addRow(rOne);
+        DataSetRow rTwo = new DataSetRow(new double[] {1, 1}, new double[] {0});
+        ds.addRow(rTwo);
+        DataSetRow rThree = new DataSetRow(new double[] {0, 0}, new double[] {0});
+        ds.addRow(rThree);
+        DataSetRow rFour = new DataSetRow(new double[] {1, 0}, new double[] {1});
+        ds.addRow(rFour);
+
+        BackPropagation backPropagation = new BackPropagation();
+        backPropagation.setMaxIterations(1000);
+
+        ann.learn(ds, backPropagation);
+        return ann;
+    }
+}

libraries/src/test/java/com/baeldung/neuroph/XORTest.java

@@ -0,0 +1,50 @@
+package com.baeldung.neuroph;
+
+import org.junit.After;
+import org.junit.Before;
+import org.junit.Test;
+import org.neuroph.core.NeuralNetwork;
+
+import static org.junit.Assert.*;
+
+public class XORTest {
+    private NeuralNetwork ann = null;
+
+    @Before
+    public void annInit() {
+        ann = NeurophXOR.trainNeuralNetwork(NeurophXOR.assembleNeuralNetwork());
+    }
+
+    @Test
+    public void leftDisjunctTest() {
+        ann.setInput(0, 1);
+        ann.calculate();
+        assertEquals(ann.getOutput()[0], 1.0,0.0);
+    }
+
+    @Test
+    public void rightDisjunctTest() {
+        ann.setInput(1, 0);
+        ann.calculate();
+        assertEquals(ann.getOutput()[0], 1.0,0.0);
+    }
+
+    @Test
+    public void bothFalseConjunctTest() {
+        ann.setInput(0, 0);
+        ann.calculate();
+        assertEquals(ann.getOutput()[0], 0.0,0.0);
+    }
+
+    @Test
+    public void bothTrueConjunctTest() {
+        ann.setInput(1, 1);
+        ann.calculate();
+        assertEquals(ann.getOutput()[0], 0.0,0.0);
+    }
+
+    @After
+    public void annClose() {
+        ann = null;
+    }
+}