Author: tommaso
Date: Wed Jun 19 11:44:55 2013
New Revision: 1494566
URL: http://svn.apache.org/r1494566
Log:
backprop test now using 0.5M random inputs
Modified:
labs/yay/trunk/core/src/main/java/org/apache/yay/core/BackPropagationLearningStrategy.java
labs/yay/trunk/core/src/test/java/org/apache/yay/core/BackPropagationLearningStrategyTest.java
Modified:
labs/yay/trunk/core/src/main/java/org/apache/yay/core/BackPropagationLearningStrategy.java
URL:
http://svn.apache.org/viewvc/labs/yay/trunk/core/src/main/java/org/apache/yay/core/BackPropagationLearningStrategy.java?rev=1494566&r1=1494565&r2=1494566&view=diff
==============================================================================
---
labs/yay/trunk/core/src/main/java/org/apache/yay/core/BackPropagationLearningStrategy.java
(original)
+++
labs/yay/trunk/core/src/main/java/org/apache/yay/core/BackPropagationLearningStrategy.java
Wed Jun 19 11:44:55 2013
@@ -80,7 +80,7 @@ public class BackPropagationLearningStra
if (newCost > cost) {
throw new RuntimeException("failed to converge at iteration " +
iterations + " with alpha "+ alpha +" : cost going from " + cost + " to " +
newCost);
} else if (cost == newCost || newCost < threshold || iterations >
MAX_ITERATIONS) {
- System.out.println("successfully converged after " + iterations + "
iterations with cost " + newCost + " and parameters " +
Arrays.toString(hypothesis.getParameters()));
+ System.out.println("successfully converged with alpha " + alpha + "
after " + iterations + " iterations with cost " + newCost + " and parameters "
+ Arrays.toString(hypothesis.getParameters()));
break;
}
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=1494566&r1=1494565&r2=1494566&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 11:44:55 2013
@@ -60,10 +60,10 @@ public class BackPropagationLearningStra
}
@Test
- public void testLearningWithRandomSamplesAndRandomWeightsAndParams() throws
Exception {
+ public void testBigLearningWithRandomParameters() throws Exception {
PredictionStrategy<Double, Double> predictionStrategy = new
FeedForwardStrategy(new SigmoidFunction());
BackPropagationLearningStrategy backPropagationLearningStrategy =
- new BackPropagationLearningStrategy(0.1d, 0.001d,
predictionStrategy, new LogisticRegressionCostFunction(Math.random()));
+ new BackPropagationLearningStrategy(Math.random(), 0.00001d,
predictionStrategy, new LogisticRegressionCostFunction(Math.random()));
// 3 input units, 3 hidden units, 4 hidden units, 1 output unit
RealMatrix[] initialWeights = new RealMatrix[3];
@@ -71,7 +71,7 @@ public class BackPropagationLearningStra
initialWeights[1] = new Array2DRowRealMatrix(new double[][]{{0d, 0d, 0d,
0d}, {1d, Math.random(), Math.random(), Math.random()}, {1d, Math.random(),
Math.random(), Math.random()}, {1d, Math.random(), Math.random(),
Math.random()}});
initialWeights[2] = new Array2DRowRealMatrix(new
double[][]{{1d,Math.random(), Math.random(), Math.random()}});
- Collection<TrainingExample<Double, Double>> samples = createSamples(50, 2);
+ Collection<TrainingExample<Double, Double>> samples =
createSamples(500000, 2);
TrainingSet<Double, Double> trainingSet = new TrainingSet<Double,
Double>(samples);
RealMatrix[] learntWeights =
backPropagationLearningStrategy.learnWeights(initialWeights, trainingSet);
assertNotNull(learntWeights);
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