Author: tommaso
Date: Thu Nov 12 16:11:25 2015
New Revision: 1714080
URL: http://svn.apache.org/viewvc?rev=1714080&view=rev
Log:
added cross-entropy cost function
Added:
labs/yay/trunk/core/src/main/java/org/apache/yay/core/CrossEntropyCostFunction.java
(with props)
Modified:
labs/yay/trunk/core/src/test/java/org/apache/yay/core/WordVectorsTest.java
Added:
labs/yay/trunk/core/src/main/java/org/apache/yay/core/CrossEntropyCostFunction.java
URL:
http://svn.apache.org/viewvc/labs/yay/trunk/core/src/main/java/org/apache/yay/core/CrossEntropyCostFunction.java?rev=1714080&view=auto
==============================================================================
---
labs/yay/trunk/core/src/main/java/org/apache/yay/core/CrossEntropyCostFunction.java
(added)
+++
labs/yay/trunk/core/src/main/java/org/apache/yay/core/CrossEntropyCostFunction.java
Thu Nov 12 16:11:25 2015
@@ -0,0 +1,65 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+package org.apache.yay.core;
+
+import org.apache.commons.math3.linear.RealMatrix;
+import org.apache.yay.Hypothesis;
+import org.apache.yay.NeuralNetworkCostFunction;
+import org.apache.yay.PredictionException;
+import org.apache.yay.TrainingExample;
+import org.apache.yay.TrainingSet;
+
+/**
+ * This calculates the cross entropy cost function for neural networks
+ */
+public class CrossEntropyCostFunction implements NeuralNetworkCostFunction {
+
+ @Override
+ public Double calculateAggregatedCost(TrainingSet<Double, Double>
trainingSet,
+ Hypothesis<RealMatrix, Double, Double>
hypothesis) throws Exception {
+ TrainingExample<Double, Double>[] samples = new
TrainingExample[trainingSet.size()];
+ int i = 0;
+ for (TrainingExample<Double, Double> sample : trainingSet) {
+ samples[i] = sample;
+ i++;
+ }
+ return calculateCost(hypothesis, samples);
+ }
+
+ private Double calculateErrorTerm(Hypothesis<RealMatrix, Double, Double>
hypothesis,
+ TrainingExample<Double, Double>...
trainingExamples) throws PredictionException {
+ Double res = 0d;
+
+ for (TrainingExample<Double, Double> input : trainingExamples) {
+ Double[] predictedOutput = hypothesis.predict(input);
+ Double[] sampleOutput = input.getOutput();
+ for (int i = 0; i < predictedOutput.length; i++) {
+ Double so = sampleOutput[i];
+ Double po = predictedOutput[i];
+ res -= so * Math.log(po);
+ }
+ }
+ return res;
+ }
+
+ @Override
+ public Double calculateCost(Hypothesis<RealMatrix, Double, Double>
hypothesis, TrainingExample<Double, Double>... trainingExamples) throws
Exception {
+ return calculateErrorTerm(hypothesis, trainingExamples);
+ }
+}
Propchange:
labs/yay/trunk/core/src/main/java/org/apache/yay/core/CrossEntropyCostFunction.java
------------------------------------------------------------------------------
svn:eol-style = native
Modified:
labs/yay/trunk/core/src/test/java/org/apache/yay/core/WordVectorsTest.java
URL:
http://svn.apache.org/viewvc/labs/yay/trunk/core/src/test/java/org/apache/yay/core/WordVectorsTest.java?rev=1714080&r1=1714079&r2=1714080&view=diff
==============================================================================
--- labs/yay/trunk/core/src/test/java/org/apache/yay/core/WordVectorsTest.java
(original)
+++ labs/yay/trunk/core/src/test/java/org/apache/yay/core/WordVectorsTest.java
Thu Nov 12 16:11:25 2015
@@ -105,7 +105,7 @@ public class WordVectorsTest {
activationFunctions.put(1, new SoftmaxActivationFunction());
FeedForwardStrategy predictionStrategy = new
FeedForwardStrategy(activationFunctions);
BackPropagationLearningStrategy learningStrategy = new
BackPropagationLearningStrategy(0.01d, 1,
- BackPropagationLearningStrategy.DEFAULT_THRESHOLD,
predictionStrategy, new LogisticRegressionCostFunction(),
+ BackPropagationLearningStrategy.DEFAULT_THRESHOLD,
predictionStrategy, new CrossEntropyCostFunction(),
trainingSet.size());
NeuralNetwork neuralNetwork = NeuralNetworkFactory.create(randomWeights,
learningStrategy, predictionStrategy);
@@ -238,9 +238,8 @@ public class WordVectorsTest {
}
}
- private TrainingSet<Double, Double> createTrainingSet(final List<String>
vocabulary, Queue<List<byte[]>> fragments, int window) {
+ private TrainingSet<Double, Double> createTrainingSet(final List<String>
vocabulary, Queue<List<byte[]>> fragments, int window) throws IOException {
long start = System.currentTimeMillis();
- Path file = Paths.get("/Users/teofili/Desktop/ts.txt");
Collection<TrainingExample<Double, Double>> samples = new LinkedList<>();
List<byte[]> fragment;
while ((fragment = fragments.poll()) != null) {
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