org.encog.neural.activation
Class ActivationLOG
java.lang.Object
org.encog.neural.activation.BasicActivationFunction
org.encog.neural.activation.ActivationLOG
- All Implemented Interfaces:
- java.io.Serializable, ActivationFunction, EncogPersistedObject
public class ActivationLOG
- extends BasicActivationFunction
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
- See Also:
- Serialized Form
| Methods inherited from class java.lang.Object |
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
ActivationLOG
public ActivationLOG()
activationFunction
public void activationFunction(double[] d)
- Implements the activation function. The array is modified according to
the activation function being used. See the class description for more
specific information on this type of activation function.
- Parameters:
d - The input array to the activation function.
clone
public java.lang.Object clone()
- Specified by:
clone in class BasicActivationFunction
- Returns:
- The object cloned.
createPersistor
public Persistor createPersistor()
- Create a Persistor for this activation function.
- Specified by:
createPersistor in interface EncogPersistedObject- Specified by:
createPersistor in class BasicActivationFunction
- Returns:
- The persistor.
derivativeFunction
public void derivativeFunction(double[] d)
- Implements the activation function derivative. The array is modified
according derivative of the activation function being used. See the class
description for more specific information on this type of activation
function. Propagation training requires the derivative. Some activation
functions do not support a derivative and will throw an error.
- Parameters:
d - The input array to the activation function.
hasDerivative
public boolean hasDerivative()
- Returns:
- Return true, log has a derivative.