Author: tommaso
Date: Fri Aug 2 07:52:23 2013
New Revision: 1509575
URL: http://svn.apache.org/r1509575
Log:
upgraded BasicPerceptronTest
Modified:
labs/yay/trunk/core/src/test/java/org/apache/yay/core/BasicPerceptronTest.java
Modified:
labs/yay/trunk/core/src/test/java/org/apache/yay/core/BasicPerceptronTest.java
URL:
http://svn.apache.org/viewvc/labs/yay/trunk/core/src/test/java/org/apache/yay/core/BasicPerceptronTest.java?rev=1509575&r1=1509574&r2=1509575&view=diff
==============================================================================
---
labs/yay/trunk/core/src/test/java/org/apache/yay/core/BasicPerceptronTest.java
(original)
+++
labs/yay/trunk/core/src/test/java/org/apache/yay/core/BasicPerceptronTest.java
Fri Aug 2 07:52:23 2013
@@ -21,6 +21,7 @@ package org.apache.yay.core;
import java.util.ArrayList;
import java.util.Collection;
import java.util.LinkedList;
+import java.util.Random;
import org.apache.yay.Feature;
import org.apache.yay.TrainingExample;
@@ -29,13 +30,15 @@ import org.junit.Before;
import org.junit.Test;
import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertTrue;
/**
* Testcase for {@link org.apache.yay.core.BasicPerceptron}
*/
public class BasicPerceptronTest {
- private TrainingSet<Double, Double> dataset;
+ private TrainingSet<Double, Double> smallDataset;
+ private TrainingSet<Double, Double> bigDataset;
@Before
public void setUp() throws Exception {
@@ -44,21 +47,67 @@ public class BasicPerceptronTest {
samples.add(createTrainingExample(1d, 5d, 6d, 0.5d));
samples.add(createTrainingExample(0.1d, 9d, 4d, 1.9d));
samples.add(createTrainingExample(0.11d, 4d, 2.6d, 9.5d));
- dataset = new TrainingSet<Double,Double>(samples);
+ smallDataset = new TrainingSet<Double,Double>(samples);
+
+ Collection<TrainingExample<Double, Double>> samples1 = new
LinkedList<TrainingExample<Double, Double>>() ;
+ Random r = new Random();
+ for (int i = 0; i < 100000; i++) {
+ samples1.add(createTrainingExample(1d, r.nextDouble(),
+ r.nextDouble(), r.nextDouble(), r.nextDouble(), r.nextDouble(),
+ r.nextDouble(), r.nextDouble(), r.nextDouble(), r.nextDouble(),
+ r.nextDouble(), r.nextDouble(), r.nextDouble(), r.nextDouble(),
+ r.nextDouble(), r.nextDouble(), r.nextDouble(), r.nextDouble(),
+ r.nextDouble(), r.nextDouble()));
+ }
+ bigDataset = new TrainingSet<Double,Double>(samples1);
+
}
@Test
@SuppressWarnings("unchecked")
- public void testLearnPhase() throws Exception {
- BasicPerceptron basicPerceptron = new BasicPerceptron(1d, 2d, 3d, 4d);
- basicPerceptron.learn(dataset);
+ public void testLearnPhaseWithBigDataset() throws Exception {
+ Random r = new Random();
+ BasicPerceptron basicPerceptron = new BasicPerceptron(1d, r.nextDouble(),
+ r.nextDouble(), r.nextDouble(), r.nextDouble(), r.nextDouble(),
+ r.nextDouble(), r.nextDouble(), r.nextDouble(), r.nextDouble(),
+ r.nextDouble(), r.nextDouble(), r.nextDouble(), r.nextDouble(),
+ r.nextDouble(), r.nextDouble(), r.nextDouble(), r.nextDouble(),
+ r.nextDouble(), r.nextDouble());
+ basicPerceptron.learn(bigDataset);
+ }
+
+ @Test
+ @SuppressWarnings("unchecked")
+ public void testLearnAndPredictWithBigDataset() throws Exception {
+ Random r = new Random();
+ BasicPerceptron basicPerceptron = new BasicPerceptron(1d, r.nextDouble(),
+ r.nextDouble(), r.nextDouble(), r.nextDouble(), r.nextDouble(),
+ r.nextDouble(), r.nextDouble(), r.nextDouble(), r.nextDouble(),
+ r.nextDouble(), r.nextDouble(), r.nextDouble(), r.nextDouble(),
+ r.nextDouble(), r.nextDouble(), r.nextDouble(), r.nextDouble(),
+ r.nextDouble(), r.nextDouble());
+ basicPerceptron.learn(bigDataset);
+ Double output = basicPerceptron.predict(createTrainingExample(null, 1d,
+ r.nextDouble(), r.nextDouble(), r.nextDouble(), r.nextDouble(),
+ r.nextDouble(), r.nextDouble(), r.nextDouble(), r.nextDouble(),
+ r.nextDouble(), r.nextDouble(), r.nextDouble(), r.nextDouble(),
+ r.nextDouble(), r.nextDouble(), r.nextDouble(), r.nextDouble(),
+ r.nextDouble(), r.nextDouble()));
+ assertTrue(output == 0d || output == 1d);
}
@Test
@SuppressWarnings("unchecked")
- public void testPredictionPhase() throws Exception {
+ public void testLearnPhaseWithSmallDataset() throws Exception {
+ BasicPerceptron basicPerceptron = new BasicPerceptron(1d, 2d, 3d, 4d);
+ basicPerceptron.learn(smallDataset);
+}
+
+ @Test
+ @SuppressWarnings("unchecked")
+ public void testLearnAndPredictWithSmallDataset() throws Exception {
BasicPerceptron basicPerceptron = new BasicPerceptron(1d, 2d, 3d, 4d);
- basicPerceptron.learn(dataset);
+ basicPerceptron.learn(smallDataset);
Double output = basicPerceptron.predict(createTrainingExample(null, 1d,
6d, 0.4d));
assertEquals(Double.valueOf(1d), output);
}
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