org.joone.engine
Class LinearLayer

java.lang.Object
  extended by org.joone.engine.Layer
      extended by org.joone.engine.SimpleLayer
          extended by org.joone.engine.LinearLayer
All Implemented Interfaces:
java.io.Serializable, java.lang.Runnable, Learnable, LearnableLayer, NeuralLayer, Inspectable
Direct Known Subclasses:
SoftmaxLayer

public class LinearLayer
extends SimpleLayer

The output of a linear layer neuron is the sum of the weighted input values, scaled by the beta parameter. No transfer function is applied to limit the output value

See Also:
Serialized Form

Field Summary
 
Fields inherited from class org.joone.engine.Layer
bias, gradientInps, gradientOuts, inps, inputPatternListeners, learnable, learning, m_batch, monitor, myLearner, outputPatternListeners, outs, running, step, STOP_FLAG
 
Constructor Summary
LinearLayer()
          The constructor
LinearLayer(java.lang.String ElemName)
          The constructor
 
Method Summary
 void backward(double[] pattern)
          Reverse transfer function of the component.
 void forward(double[] pattern)
          Transfer function to recall a result on a trained net
 double getBeta()
          Returns the value of the beta parameter
 double getDefaultState()
          Return the default state of a node in this layer, such as 0 for a tanh or 0.5 for a sigmoid layer
 double getDerivative(int i)
          Similar to the backward message and used by RTRL
 double getMaximumState()
          Return maximum value of a node in this layer
 double getMinimumState()
          Return minimum value of a node in this layer
 java.util.Collection Inspections()
          It doesn't make sense to return biases for this layer
 void setBeta(double newBeta)
          Sets the beta value
 
Methods inherited from class org.joone.engine.SimpleLayer
getLearningRate, getLrate, getMomentum, setDimensions, setLrate, setMomentum, setMonitor
 
Methods inherited from class org.joone.engine.Layer
addInputSynapse, addNoise, addOutputSynapse, adjustSizeToFwdPattern, adjustSizeToRevPattern, check, checkInputEnabled, checkInputs, checkOutputs, copyInto, finalize, fireFwdGet, fireFwdPut, fireRevGet, fireRevPut, fwdRun, getAllInputs, getAllOutputs, getBias, getDimension, getLastGradientInps, getLastGradientOuts, getLastInputs, getLastOutputs, getLayerName, getLearner, getMonitor, getRows, getThreadMonitor, hasStepCounter, init, initLearner, InspectableTitle, isInputLayer, isOutputLayer, isRunning, join, randomize, randomizeBias, randomizeWeights, removeAllInputs, removeAllOutputs, removeInputSynapse, removeListener, removeOutputSynapse, resetInputListeners, revRun, run, setAllInputs, setAllOutputs, setBias, setConnDimensions, setInputDimension, setInputSynapses, setLastInputs, setLastOutputs, setLayerName, setOutputDimension, setOutputSynapses, setRows, start, stop, sumBackInput, sumInput, toString
 
Methods inherited from class java.lang.Object
clone, equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
 

Constructor Detail

LinearLayer

public LinearLayer()
The constructor


LinearLayer

public LinearLayer(java.lang.String ElemName)
The constructor

Parameters:
ElemName - The name of the Layer
Method Detail

getDerivative

public double getDerivative(int i)
Similar to the backward message and used by RTRL

Specified by:
getDerivative in class Layer

backward

public void backward(double[] pattern)
Description copied from class: Layer
Reverse transfer function of the component.

Overrides:
backward in class SimpleLayer
Parameters:
pattern - input pattern on which to apply the transfer function

forward

public void forward(double[] pattern)
Description copied from class: Layer
Transfer function to recall a result on a trained net

Specified by:
forward in class Layer
Parameters:
pattern - input pattern to which to apply the rtransfer function

getBeta

public double getBeta()
Returns the value of the beta parameter

Returns:
double - The beta parameter

setBeta

public void setBeta(double newBeta)
Sets the beta value

Parameters:
newBeta - double

Inspections

public java.util.Collection Inspections()
It doesn't make sense to return biases for this layer

Specified by:
Inspections in interface Inspectable
Overrides:
Inspections in class Layer
Returns:
null
See Also:
org.joone.Inspection

getDefaultState

public double getDefaultState()
Description copied from class: Layer
Return the default state of a node in this layer, such as 0 for a tanh or 0.5 for a sigmoid layer

Specified by:
getDefaultState in class Layer

getMinimumState

public double getMinimumState()
Description copied from class: Layer
Return minimum value of a node in this layer

Specified by:
getMinimumState in class Layer

getMaximumState

public double getMaximumState()
Description copied from class: Layer
Return maximum value of a node in this layer

Specified by:
getMaximumState in class Layer


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