/*
* Encog(tm) Core v3.4 - Java Version
* http://www.heatonresearch.com/encog/
* https://github.com/encog/encog-java-core
* Copyright 2008-2016 Heaton Research, Inc.
*
* Licensed 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.
*
* For more information on Heaton Research copyrights, licenses
* and trademarks visit:
* http://www.heatonresearch.com/copyright
*/
package org.encog.engine.network.activation;
import org.encog.mathutil.BoundMath;
import org.encog.ml.factory.MLActivationFactory;
import org.encog.util.obj.ActivationUtil;
/**
* An activation function based on the logarithm function.
*
* This type of activation function can be useful to prevent saturation. A
* hidden node of a neural network is said to be saturated on a given set of
* inputs when its output is approximately 1 or -1 "most of the time". If this
* phenomena occurs during training then the learning of the network can be
* slowed significantly since the error surface is very at in this instance.
*
* @author jheaton
*
*/
public class ActivationLOG implements ActivationFunction {
/**
* The serial id.
*/
private static final long serialVersionUID = 7134233791725797522L;
/**
* The parameters.
*/
private final double[] params;
/**
* Construct the activation function.
*/
public ActivationLOG() {
this.params = new double[0];
}
/**
* {@inheritDoc}
*/
@Override
public final void activationFunction(final double[] x, final int start,
final int size) {
for (int i = start; i < start + size; i++) {
if (x[i] >= 0) {
x[i] = BoundMath.log(1 + x[i]);
} else {
x[i] = -BoundMath.log(1 - x[i]);
}
}
}
/**
* @return The object cloned.
*/
@Override
public final ActivationFunction clone() {
return new ActivationLOG();
}
/**
* {@inheritDoc}
*/
@Override
public final double derivativeFunction(final double b, final double a) {
if (b >= 0) {
return 1 / (1 + b);
} else {
return 1 / (1 - b);
}
}
/**
* {@inheritDoc}
*/
@Override
public final String[] getParamNames() {
final String[] result = {};
return result;
}
/**
* {@inheritDoc}
*/
@Override
public final double[] getParams() {
return this.params;
}
/**
* @return Return true, log has a derivative.
*/
@Override
public final boolean hasDerivative() {
return true;
}
/**
* {@inheritDoc}
*/
@Override
public final void setParam(final int index, final double value) {
this.params[index] = value;
}
/**
* {@inheritDoc}
*/
@Override
public String getFactoryCode() {
return ActivationUtil.generateActivationFactory(MLActivationFactory.AF_LOG, this);
}
@Override
public String getLabel() {
return "log";
}
}