Author: tommaso
Date: Wed Jun 19 11:57:11 2013
New Revision: 1494572
URL: http://svn.apache.org/r1494572
Log:
added test for default settings
Modified:
labs/yay/trunk/core/src/test/java/org/apache/yay/core/BackPropagationLearningStrategyTest.java
Modified:
labs/yay/trunk/core/src/test/java/org/apache/yay/core/BackPropagationLearningStrategyTest.java
URL:
http://svn.apache.org/viewvc/labs/yay/trunk/core/src/test/java/org/apache/yay/core/BackPropagationLearningStrategyTest.java?rev=1494572&r1=1494571&r2=1494572&view=diff
==============================================================================
---
labs/yay/trunk/core/src/test/java/org/apache/yay/core/BackPropagationLearningStrategyTest.java
(original)
+++
labs/yay/trunk/core/src/test/java/org/apache/yay/core/BackPropagationLearningStrategyTest.java
Wed Jun 19 11:57:11 2013
@@ -37,6 +37,27 @@ import static junit.framework.Assert.ass
*/
public class BackPropagationLearningStrategyTest {
+
+ @Test
+ public void testLearningWithDefaultSettingsAndRandomSamples() throws
Exception {
+ BackPropagationLearningStrategy backPropagationLearningStrategy = new
BackPropagationLearningStrategy();
+
+ // 3 input units, 3 hidden units, 4 hidden units, 1 output unit
+ RealMatrix[] initialWeights = new RealMatrix[3];
+ initialWeights[0] = new Array2DRowRealMatrix(new double[][]{{0d, 0d, 0d},
{1d, 0.6d, 3d}, {1d, 2d, 2d}, {1d, 0.6d, 3d}});
+ initialWeights[1] = new Array2DRowRealMatrix(new double[][]{{0d, 0d, 0d,
0d}, {1d, 0.5d, 1d, 0.5d}, {1d, 0.1d, 8d, 0.1d}, {1d, 0.1d, 8d, 0.2d}});
+ initialWeights[2] = new Array2DRowRealMatrix(new double[][]{{1d, 2d, 0.3d,
0.5d}});
+
+ Collection<TrainingExample<Double, Double>> samples = createSamples(1000,
2);
+ TrainingSet<Double, Double> trainingSet = new TrainingSet<Double,
Double>(samples);
+ RealMatrix[] learntWeights =
backPropagationLearningStrategy.learnWeights(initialWeights, trainingSet);
+ assertNotNull(learntWeights);
+
+ assertFalse(learntWeights[0].equals(initialWeights[0]));
+ assertFalse(learntWeights[1].equals(initialWeights[1]));
+ assertFalse(learntWeights[2].equals(initialWeights[2]));
+ }
+
@Test
public void testLearningWithRandomSamples() throws Exception {
PredictionStrategy<Double, Double> predictionStrategy = new
FeedForwardStrategy(new SigmoidFunction());
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