Author: tommaso
Date: Fri Oct 9 06:51:24 2015
New Revision: 1707664
URL: http://svn.apache.org/viewvc?rev=1707664&view=rev
Log:
more appropriate test name, using sigmoid on output layer until softmax is there
Added:
labs/yay/trunk/core/src/test/java/org/apache/yay/core/WordVectorsTest.java
- copied, changed from r1707564,
labs/yay/trunk/core/src/test/java/org/apache/yay/core/Word2VecTest.java
Removed:
labs/yay/trunk/core/src/test/java/org/apache/yay/core/Word2VecTest.java
Copied:
labs/yay/trunk/core/src/test/java/org/apache/yay/core/WordVectorsTest.java
(from r1707564,
labs/yay/trunk/core/src/test/java/org/apache/yay/core/Word2VecTest.java)
URL:
http://svn.apache.org/viewvc/labs/yay/trunk/core/src/test/java/org/apache/yay/core/WordVectorsTest.java?p2=labs/yay/trunk/core/src/test/java/org/apache/yay/core/WordVectorsTest.java&p1=labs/yay/trunk/core/src/test/java/org/apache/yay/core/Word2VecTest.java&r1=1707564&r2=1707664&rev=1707664&view=diff
==============================================================================
--- labs/yay/trunk/core/src/test/java/org/apache/yay/core/Word2VecTest.java
(original)
+++ labs/yay/trunk/core/src/test/java/org/apache/yay/core/WordVectorsTest.java
Fri Oct 9 06:51:24 2015
@@ -53,7 +53,7 @@ import static org.junit.Assert.*;
/**
* Integration test for using Yay to implement word vectors algorithms.
*/
-public class Word2VecTest {
+public class WordVectorsTest {
@Test
public void testSGM() throws Exception {
@@ -76,7 +76,7 @@ public class Word2VecTest {
Map<Integer, ActivationFunction<Double>> activationFunctions = new
HashMap<Integer, ActivationFunction<Double>>();
activationFunctions.put(0, new IdentityActivationFunction<Double>());
// TODO : place a softmax activation for the output layer
- activationFunctions.put(0, new IdentityActivationFunction<Double>());
+ activationFunctions.put(1, new SigmoidFunction());
FeedForwardStrategy predictionStrategy = new
FeedForwardStrategy(activationFunctions);
BackPropagationLearningStrategy learningStrategy = new
BackPropagationLearningStrategy(0.05d, 10,
BackPropagationLearningStrategy.DEFAULT_THRESHOLD,
predictionStrategy, new LMSCostFunction(),
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