org.encog.neural.activation
Class ActivationLinear
java.lang.Object
org.encog.neural.activation.BasicActivationFunction
org.encog.neural.activation.ActivationLinear
- All Implemented Interfaces:
- java.io.Serializable, java.lang.Cloneable, ActivationFunction, EncogPersistedObject
public class ActivationLinear
- extends BasicActivationFunction
The Linear layer is really not an activation function at all. The input is
simply passed on, unmodified, to the output. This activation function is
primarily theoretical and of little actual use. Usually an activation
function that scales between 0 and 1 or -1 and 1 should be used.
- See Also:
- Serialized Form
| Methods inherited from class java.lang.Object |
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
ActivationLinear
public ActivationLinear()
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 interface EncogPersistedObject- Overrides:
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- Overrides:
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 false, linear has no derivative.