org.encog.neural.pnn
public abstract class AbstractPNN extends BasicML
Constructor and Description |
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AbstractPNN(PNNKernelType kernel,
PNNOutputMode outputMode,
int inputCount,
int outputCount)
Constructor.
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Modifier and Type | Method and Description |
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abstract MLData |
compute(MLData input)
Compute the output from the network.
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double[] |
getDeriv() |
double[] |
getDeriv2() |
double |
getError() |
int |
getExclude() |
int |
getInputCount() |
PNNKernelType |
getKernel() |
int |
getOutputCount() |
PNNOutputMode |
getOutputMode() |
boolean |
isSeparateClass() |
boolean |
isTrained() |
void |
resetConfusion()
Reset the confusion.
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void |
setError(double error) |
void |
setExclude(int exclude) |
void |
setSeparateClass(boolean separateClass) |
void |
setTrained(boolean trained) |
getProperties, getPropertyDouble, getPropertyLong, getPropertyString, setProperty, setProperty, setProperty, updateProperties
public AbstractPNN(PNNKernelType kernel, PNNOutputMode outputMode, int inputCount, int outputCount)
kernel
- The kernel type to use.outputMode
- The output mode to use.inputCount
- The input count.outputCount
- The output count.public abstract MLData compute(MLData input)
input
- The input to the network.public double[] getDeriv()
public double[] getDeriv2()
public double getError()
public int getExclude()
public int getInputCount()
public PNNKernelType getKernel()
public int getOutputCount()
public PNNOutputMode getOutputMode()
public boolean isTrained()
public void resetConfusion()
public void setError(double error)
error
- the error to setpublic void setExclude(int exclude)
exclude
- the exclude to setpublic void setTrained(boolean trained)
trained
- the trained to setpublic boolean isSeparateClass()
public void setSeparateClass(boolean separateClass)
separateClass
- the separateClass to setCopyright © 2014. All Rights Reserved.