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
This commit is contained in:
Adam InTae Gerard
Zeger Hendrikse
parent
a89462e7f1
commit
d4f245a275
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@ -26,6 +26,7 @@
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- [A Guide to Apache Commons DbUtils](http://www.baeldung.com/apache-commons-dbutils)
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- [Introduction to Awaitility](http://www.baeldung.com/awaitlity-testing)
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- [Guide to the HyperLogLog Algorithm](http://www.baeldung.com/java-hyperloglog)
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- [Introduction to Neuroph](http://www.baeldung.com/intro-to-neuroph)
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The libraries module contains examples related to small libraries that are relatively easy to use and does not require any separate module of its own.
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@ -7,7 +7,6 @@
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<version>1.0.0-SNAPSHOT</version>
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</parent>
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<modelVersion>4.0.0</modelVersion>
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<artifactId>libraries</artifactId>
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<name>libraries</name>
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<build>
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@ -71,9 +70,51 @@
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</execution>
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</executions>
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</plugin>
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<!-- Neuroph -->
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<plugin>
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<groupId>org.apache.maven.plugins</groupId>
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<artifactId>maven-jar-plugin</artifactId>
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<version>3.0.2</version>
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<configuration>
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<excludes>
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<exclude>**/log4j.properties</exclude>
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</excludes>
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<archive>
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<manifest>
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<mainClass>com.baeldung.neuroph.NeurophXOR</mainClass>
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</manifest>
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</archive>
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</configuration>
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</plugin>
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<plugin>
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<groupId>org.apache.maven.plugins</groupId>
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<artifactId>maven-surefire-plugin</artifactId>
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<version>2.18.1</version>
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<executions>
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<execution>
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<id>test</id>
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<phase>test</phase>
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<goals>
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<goal>test</goal>
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</goals>
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<configuration>
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<includes>
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<include>test/java/com/baeldung/neuroph/XORTest.java</include>
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</includes>
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</configuration>
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</execution>
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</executions>
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</plugin>
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<!-- /Neuroph -->
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</plugins>
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</build>
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<dependencies>
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<!-- https://mvnrepository.com/artifact/org.beykery/neuroph/2.92 -->
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<dependency>
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<groupId>org.beykery</groupId>
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<artifactId>neuroph</artifactId>
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<version>${neuroph.version}</version>
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</dependency>
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<!-- https://mvnrepository.com/artifact/cglib/cglib -->
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<dependency>
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<groupId>cglib</groupId>
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@ -327,7 +368,6 @@
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<artifactId>quartz</artifactId>
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<version>2.3.0</version>
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</dependency>
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<dependency>
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<groupId>one.util</groupId>
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<artifactId>streamex</artifactId>
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@ -432,6 +472,7 @@
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<commons.io.version>2.5</commons.io.version>
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<flink.version>1.2.0</flink.version>
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<jackson.version>2.8.5</jackson.version>
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<neuroph.version>2.92</neuroph.version>
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<serenity.version>1.4.0</serenity.version>
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<serenity.jbehave.version>1.24.0</serenity.jbehave.version>
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<serenity.jira.version>1.1.3-rc.5</serenity.jira.version>
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@ -0,0 +1,73 @@
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package com.baeldung.neuroph;
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import org.neuroph.core.Layer;
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import org.neuroph.core.NeuralNetwork;
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import org.neuroph.core.Neuron;
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import org.neuroph.core.data.DataSet;
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import org.neuroph.core.data.DataSetRow;
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import org.neuroph.nnet.learning.BackPropagation;
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import org.neuroph.util.ConnectionFactory;
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import org.neuroph.util.NeuralNetworkType;
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public class NeurophXOR {
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public static NeuralNetwork assembleNeuralNetwork() {
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Layer inputLayer = new Layer();
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inputLayer.addNeuron(new Neuron());
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inputLayer.addNeuron(new Neuron());
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Layer hiddenLayerOne = new Layer();
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hiddenLayerOne.addNeuron(new Neuron());
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hiddenLayerOne.addNeuron(new Neuron());
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hiddenLayerOne.addNeuron(new Neuron());
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hiddenLayerOne.addNeuron(new Neuron());
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Layer hiddenLayerTwo = new Layer();
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hiddenLayerTwo.addNeuron(new Neuron());
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hiddenLayerTwo.addNeuron(new Neuron());
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hiddenLayerTwo.addNeuron(new Neuron());
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hiddenLayerTwo.addNeuron(new Neuron());
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Layer outputLayer = new Layer();
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outputLayer.addNeuron(new Neuron());
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NeuralNetwork ann = new NeuralNetwork();
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ann.addLayer(0, inputLayer);
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ann.addLayer(1, hiddenLayerOne);
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ConnectionFactory.fullConnect(ann.getLayerAt(0), ann.getLayerAt(1));
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ann.addLayer(2, hiddenLayerTwo);
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ConnectionFactory.fullConnect(ann.getLayerAt(1), ann.getLayerAt(2));
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ann.addLayer(3, outputLayer);
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ConnectionFactory.fullConnect(ann.getLayerAt(2), ann.getLayerAt(3));
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ConnectionFactory.fullConnect(ann.getLayerAt(0), ann.getLayerAt(ann.getLayersCount()-1), false);
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ann.setInputNeurons(inputLayer.getNeurons());
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ann.setOutputNeurons(outputLayer.getNeurons());
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ann.setNetworkType(NeuralNetworkType.MULTI_LAYER_PERCEPTRON);
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return ann;
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}
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public static NeuralNetwork trainNeuralNetwork(NeuralNetwork ann) {
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int inputSize = 2;
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int outputSize = 1;
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DataSet ds = new DataSet(inputSize, outputSize);
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DataSetRow rOne = new DataSetRow(new double[] {0, 1}, new double[] {1});
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ds.addRow(rOne);
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DataSetRow rTwo = new DataSetRow(new double[] {1, 1}, new double[] {0});
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ds.addRow(rTwo);
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DataSetRow rThree = new DataSetRow(new double[] {0, 0}, new double[] {0});
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ds.addRow(rThree);
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DataSetRow rFour = new DataSetRow(new double[] {1, 0}, new double[] {1});
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ds.addRow(rFour);
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BackPropagation backPropagation = new BackPropagation();
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backPropagation.setMaxIterations(1000);
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ann.learn(ds, backPropagation);
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return ann;
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}
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}
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@ -0,0 +1,50 @@
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package com.baeldung.neuroph;
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import org.junit.After;
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import org.junit.Before;
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import org.junit.Test;
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import org.neuroph.core.NeuralNetwork;
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import static org.junit.Assert.*;
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public class XORTest {
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private NeuralNetwork ann = null;
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@Before
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public void annInit() {
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ann = NeurophXOR.trainNeuralNetwork(NeurophXOR.assembleNeuralNetwork());
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}
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@Test
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public void leftDisjunctTest() {
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ann.setInput(0, 1);
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ann.calculate();
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assertEquals(ann.getOutput()[0], 1.0,0.0);
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}
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@Test
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public void rightDisjunctTest() {
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ann.setInput(1, 0);
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ann.calculate();
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assertEquals(ann.getOutput()[0], 1.0,0.0);
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}
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@Test
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public void bothFalseConjunctTest() {
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ann.setInput(0, 0);
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ann.calculate();
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assertEquals(ann.getOutput()[0], 0.0,0.0);
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}
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@Test
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public void bothTrueConjunctTest() {
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ann.setInput(1, 1);
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ann.calculate();
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assertEquals(ann.getOutput()[0], 0.0,0.0);
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}
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@After
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public void annClose() {
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ann = null;
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}
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}
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