Author: tommaso
Date: Fri Jan 15 11:44:14 2016
New Revision: 1724779
URL: http://svn.apache.org/viewvc?rev=1724779&view=rev
Log:
fixed bug in SFFNN, added boolean operator NNs tests
Modified:
labs/yay/trunk/core/src/main/java/org/apache/yay/ShallowFeedForwardNeuralNetwork.java
labs/yay/trunk/core/src/test/java/org/apache/yay/ShallowFeedForwardNeuralNetworkTest.java
Modified:
labs/yay/trunk/core/src/main/java/org/apache/yay/ShallowFeedForwardNeuralNetwork.java
URL:
http://svn.apache.org/viewvc/labs/yay/trunk/core/src/main/java/org/apache/yay/ShallowFeedForwardNeuralNetwork.java?rev=1724779&r1=1724778&r2=1724779&view=diff
==============================================================================
---
labs/yay/trunk/core/src/main/java/org/apache/yay/ShallowFeedForwardNeuralNetwork.java
(original)
+++
labs/yay/trunk/core/src/main/java/org/apache/yay/ShallowFeedForwardNeuralNetwork.java
Fri Jan 15 11:44:14 2016
@@ -18,7 +18,6 @@
*/
package org.apache.yay;
-import org.apache.commons.lang3.SystemUtils;
import org.apache.commons.math3.linear.ArrayRealVector;
import org.apache.commons.math3.linear.MatrixUtils;
import org.apache.commons.math3.linear.RealMatrix;
@@ -54,11 +53,12 @@ public class ShallowFeedForwardNeuralNet
public ShallowFeedForwardNeuralNetwork(Configuration configuration) {
this.configuration = configuration;
- initialize();
+ this.weights = createRandomWeights();
}
- private void initialize() {
- weights = createRandomWeights();
+ public ShallowFeedForwardNeuralNetwork(Configuration configuration,
RealMatrix[] weights) {
+ this.configuration = configuration;
+ this.weights = weights;
}
private RealMatrix[] createRandomWeights() {
@@ -338,7 +338,6 @@ public class ShallowFeedForwardNeuralNet
// apply the activation function to each element in the matrix
x =
configuration.activationFunctions[idx].applyMatrix(x.getRowMatrix(0));
- x = new SigmoidFunction().applyMatrix(x.getRowMatrix(0));
debugOutput[w] = x.getRowVector(0);
}
Modified:
labs/yay/trunk/core/src/test/java/org/apache/yay/ShallowFeedForwardNeuralNetworkTest.java
URL:
http://svn.apache.org/viewvc/labs/yay/trunk/core/src/test/java/org/apache/yay/ShallowFeedForwardNeuralNetworkTest.java?rev=1724779&r1=1724778&r2=1724779&view=diff
==============================================================================
---
labs/yay/trunk/core/src/test/java/org/apache/yay/ShallowFeedForwardNeuralNetworkTest.java
(original)
+++
labs/yay/trunk/core/src/test/java/org/apache/yay/ShallowFeedForwardNeuralNetworkTest.java
Fri Jan 15 11:44:14 2016
@@ -18,6 +18,8 @@
*/
package org.apache.yay;
+import org.apache.commons.math3.linear.Array2DRowRealMatrix;
+import org.apache.commons.math3.linear.RealMatrix;
import org.junit.Test;
import static org.junit.Assert.assertEquals;
@@ -60,6 +62,89 @@ public class ShallowFeedForwardNeuralNet
double[] doubles = neuralNetwork.predictOutput(new double[]{0.7d, 0.8d,
0.9d});
assertNotNull(doubles);
- assertEquals(0.4d, doubles[0], 0.4d);
+ assertEquals(0.9d, doubles[0], 0.2d);
}
+
+ @Test
+ public void andNNCreationTest() throws Exception {
+ double[][] weights = {{-30d, 20d, 20d}};
+ RealMatrix singleAndLayerWeights = new Array2DRowRealMatrix(weights);
+ RealMatrix[] andRealMatrixSet = new RealMatrix[]{singleAndLayerWeights};
+
+ ShallowFeedForwardNeuralNetwork.Configuration configuration = new
ShallowFeedForwardNeuralNetwork.Configuration();
+ configuration.alpha = 0.0001d;
+ configuration.layers = new int[]{2, 1};
+ configuration.maxIterations = 10000;
+ configuration.threshold = 0.004d;
+ configuration.activationFunctions = new ActivationFunction[]{new
SigmoidFunction()};
+
+ ShallowFeedForwardNeuralNetwork and = new
ShallowFeedForwardNeuralNetwork(configuration, andRealMatrixSet);
+
+ assertEquals(0L, Math.round(and.predictOutput(new double[]{1d, 0d})[0]));
+ assertEquals(0L, Math.round(and.predictOutput(new double[]{0d, 1d})[0]));
+ assertEquals(0L, Math.round(and.predictOutput(new double[]{0d, 0d})[0]));
+ assertEquals(1L, Math.round(and.predictOutput(new double[]{1d, 1d})[0]));
+ }
+
+ @Test
+ public void orNNCreationTest() throws Exception {
+ double[][] weights = {{-10d, 20d, 20d}};
+ RealMatrix singleOrLayerWeights = new Array2DRowRealMatrix(weights);
+ RealMatrix[] orRealMatrixSet = new RealMatrix[]{singleOrLayerWeights};
+
+ ShallowFeedForwardNeuralNetwork.Configuration configuration = new
ShallowFeedForwardNeuralNetwork.Configuration();
+ configuration.alpha = 0.0001d;
+ configuration.layers = new int[]{2, 1};
+ configuration.maxIterations = 10000;
+ configuration.threshold = 0.004d;
+ configuration.activationFunctions = new ActivationFunction[]{new
SigmoidFunction()};
+
+ ShallowFeedForwardNeuralNetwork or = new
ShallowFeedForwardNeuralNetwork(configuration, orRealMatrixSet);
+
+ assertEquals(1L, Math.round(or.predictOutput(new double[]{1d, 0d})[0]));
+ assertEquals(1L, Math.round(or.predictOutput(new double[]{0d, 1d})[0]));
+ assertEquals(1L, Math.round(or.predictOutput(new double[]{1d, 1d})[0]));
+ assertEquals(0L, Math.round(or.predictOutput(new double[]{0d, 0d})[0]));
+ }
+
+ @Test
+ public void notNNCreationTest() throws Exception {
+ double[][] weights = {{10d, -20d}};
+ RealMatrix singleNotLayerWeights = new Array2DRowRealMatrix(weights);
+ RealMatrix[] notRealMatrixSet = new RealMatrix[]{singleNotLayerWeights};
+
+ ShallowFeedForwardNeuralNetwork.Configuration configuration = new
ShallowFeedForwardNeuralNetwork.Configuration();
+ configuration.alpha = 0.0001d;
+ configuration.layers = new int[]{1, 1};
+ configuration.maxIterations = 10000;
+ configuration.threshold = 0.004d;
+ configuration.activationFunctions = new ActivationFunction[]{new
SigmoidFunction()};
+
+ ShallowFeedForwardNeuralNetwork not = new
ShallowFeedForwardNeuralNetwork(configuration, notRealMatrixSet);
+ assertEquals(1L, Math.round(not.predictOutput(new double[]{0d})[0]));
+ assertEquals(0L, Math.round(not.predictOutput(new double[]{1d})[0]));
+ }
+
+ @Test
+ public void norNNCreationTest() throws Exception {
+ RealMatrix firstNorLayerWeights = new Array2DRowRealMatrix(new
double[][]{{0, 0, 0}, {-30d, 20d, 20d}, {10d, -20d, -20d}});
+ RealMatrix secondNorLayerWeights = new Array2DRowRealMatrix(new
double[][]{{-10d, 20d, 20d}});
+ RealMatrix[] norRealMatrixSet = new RealMatrix[]{firstNorLayerWeights,
secondNorLayerWeights};
+
+ ShallowFeedForwardNeuralNetwork.Configuration configuration = new
ShallowFeedForwardNeuralNetwork.Configuration();
+ configuration.alpha = 0.0001d;
+ configuration.layers = new int[]{2, 2, 1};
+ configuration.maxIterations = 10000;
+ configuration.threshold = 0.004d;
+ configuration.activationFunctions = new ActivationFunction[]{new
SigmoidFunction()};
+
+ ShallowFeedForwardNeuralNetwork nor = new
ShallowFeedForwardNeuralNetwork(configuration, norRealMatrixSet);
+
+
+ assertEquals(0L, Math.round(nor.predictOutput(new double[]{1d, 0d})[0]));
+ assertEquals(0L, Math.round(nor.predictOutput(new double[]{0d, 1d})[0]));
+ assertEquals(1L, Math.round(nor.predictOutput(new double[]{0d, 0d})[0]));
+ assertEquals(1L, Math.round(nor.predictOutput(new double[]{1d, 1d})[0]));
+ }
+
}
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