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java.lang.Objectorg.joone.engine.extenders.LearnerExtender
org.joone.engine.extenders.DeltaRuleExtender
org.joone.engine.extenders.RpropExtender
public class RpropExtender
This class changes the delta value in such a way that it implements the RPROP algorithm.
Field Summary | |
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protected double[][] |
theDeltas
Each weight has its own individual update-value (delta_ij(t)) represented by the next object. |
protected double[][] |
thePreviousGradients
The gradient pattern of the previous epoch (dE(t-1)/dW_ij). |
protected RpropParameters |
theRpropParameters
The parameters for the RPROP learning algorithm. |
protected double[][] |
theSummedGradients
The current som of the gradients of all patterns seen so far. |
Constructor Summary | |
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RpropExtender()
Creates a new instance of RpropExtender |
Method Summary | |
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double |
getDelta(double[] currentGradientOuts,
int j,
double aPreviousDelta)
Computes the delta value for a bias. |
double |
getDelta(double[] currentInps,
int j,
double[] currentPattern,
int k,
double aPreviousDelta)
Computes the delta value for a weight. |
RpropParameters |
getParameters()
Gets the parameters of this learning algorithm. |
void |
postBiasUpdate(double[] currentGradientOuts)
Gives extenders a change to do some post-computing after the biases are updated. |
void |
postWeightUpdate(double[] currentPattern,
double[] currentInps)
Gives extenders a change to do some post-computing after the weights are updated. |
void |
preBiasUpdate(double[] currentGradientOuts)
Gives extenders a change to do some pre-computing before the biases are updated. |
void |
preWeightUpdate(double[] currentPattern,
double[] currentInps)
Gives extenders a change to do some pre-computing before the weights are updated. |
void |
reinit()
(Re)Initializes this RPROP learner. |
void |
setParameters(RpropParameters aParameters)
Sets the parameters for this learning algorithm. |
protected double |
sign(double d)
Gets the sign of a double. |
Methods inherited from class org.joone.engine.extenders.LearnerExtender |
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getLearner, isEnabled, setEnabled, setLearner |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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protected double[][] theDeltas
protected double[][] thePreviousGradients
protected RpropParameters theRpropParameters
protected double[][] theSummedGradients
Constructor Detail |
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public RpropExtender()
Method Detail |
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public void reinit()
public double getDelta(double[] currentGradientOuts, int j, double aPreviousDelta)
DeltaRuleExtender
getDelta
in class DeltaRuleExtender
currentGradientOuts
- the back propagated gradients.j
- the index of the bias.aPreviousDelta
- a delta value calculated by a previous delta extender.public double getDelta(double[] currentInps, int j, double[] currentPattern, int k, double aPreviousDelta)
DeltaRuleExtender
getDelta
in class DeltaRuleExtender
currentInps
- the forwarded input.j
- the input index of the weight.currentPattern
- the back propagated gradients.k
- the output index of the weight.aPreviousDelta
- a delta value calculated by a previous delta extender.public void postBiasUpdate(double[] currentGradientOuts)
LearnerExtender
postBiasUpdate
in class LearnerExtender
currentGradientOuts
- the back propagated gradients.public void postWeightUpdate(double[] currentPattern, double[] currentInps)
LearnerExtender
postWeightUpdate
in class LearnerExtender
currentPattern
- the back propagated gradients.currentInps
- the forwarded input.public void preBiasUpdate(double[] currentGradientOuts)
LearnerExtender
preBiasUpdate
in class LearnerExtender
currentGradientOuts
- the back propagated gradients.public void preWeightUpdate(double[] currentPattern, double[] currentInps)
LearnerExtender
preWeightUpdate
in class LearnerExtender
currentPattern
- the back propagated gradients.currentInps
- the forwarded input.public RpropParameters getParameters()
public void setParameters(RpropParameters aParameters)
aParameters
- the parameters for this learning algorithm.protected double sign(double d)
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