com.sjm.machlearn.classifiers.neuralnets
Class BPNeuralNet

java.lang.Object
  |
  +--com.sjm.machlearn.util.MainClass
        |
        +--com.sjm.machlearn.classifiers.Classifier
              |
              +--com.sjm.machlearn.classifiers.neuralnets.BPNeuralNet

public class BPNeuralNet

extends Classifier

Field Summary

protected BPFeatureVector	feature_converter
protected double	learn_rate
protected int	nhidden
protected int	ninputs
protected int	noutputs
protected int	trainepoch
protected DoubleMatrix	whidden
protected DoubleMatrix	woutput

Fields inherited from class com.sjm.machlearn.classifiers.Classifier

Fold10Validation, JackKnifeValidation, Random10Validation

Fields inherited from class com.sjm.machlearn.util.MainClass

debug, debug_level, debug_listeners

Constructor Summary

BPNeuralNet()

BPNeuralNet(double hpercent)

Method Summary

double	activate(double value)
Feature	classify(Example example)
Classifier	cloneClassifier()
double	getAccuracy(double[][] testdata, int[] exp)
double[]	getError(double[] input, double[] exp)
double	getExampleWeight(Example example) getExampleWeight() : Returns the weight of an example for the class 0.
protected double[]	getOutput(double[] input)
protected double[]	getOutput(Example input)
double	getTotalError(double[] error)
double	getTotalError(double[] input, double[] exp)
void	initializeWeights()
void	initializeWeights(double min, double max)
java.lang.String	printClassifier()
void	reportAccuracies(int epoch, DataSet train, DataSet tune)
void	runEpoch(double[][] epoch_data, double[][] exp)
void	setParameter(int i, java.lang.Object parameter)
void	setTestSet(DataSet ts)
void	train(DataSet trainingData) train() : randomly pick 10% of trainingdata for tune set.
void	train(DataSet trainingData, DataSet tuneData)
void	trainExample(double[] input, double[] exp_output)
void	tune(DataSet trainingData, java.lang.Object[] parameters)

Methods inherited from class com.sjm.machlearn.classifiers.Classifier

doTune, generateROCCurve, getAccuracy, getBothCat, getMisCat

Methods inherited from class com.sjm.machlearn.util.MainClass

_internalError, _internalError, addDebugListener, debugMesg, debugMesg, debugMesg, debugMesg, debugMesg, debugMesg, debugOff, debugOn, internalError, internalError, setDebug, setDebugLevel

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

whidden

protected DoubleMatrix whidden

woutput

protected DoubleMatrix woutput

feature_converter

protected BPFeatureVector feature_converter

ninputs

protected int ninputs

noutputs

protected int noutputs

nhidden

protected int nhidden

learn_rate

protected double learn_rate

trainepoch

protected int trainepoch

Constructor Detail

BPNeuralNet

public BPNeuralNet()

BPNeuralNet

public BPNeuralNet(double hpercent)

Method Detail

setTestSet

public void setTestSet(DataSet ts)

initializeWeights

public void initializeWeights()

initializeWeights

public void initializeWeights(double min,
                              double max)

getOutput

protected double[] getOutput(Example input)

getOutput

protected double[] getOutput(double[] input)

getError

public double[] getError(double[] input,
                         double[] exp)

getTotalError

public double getTotalError(double[] input,
                            double[] exp)

getTotalError

public double getTotalError(double[] error)

activate

public double activate(double value)

getExampleWeight

public double getExampleWeight(Example example)

Description copied from class: Classifier

getExampleWeight() : Returns the weight of an example for the class 0. Used for ROC curves. Will be overidden.

Overrides:

getExampleWeight in class Classifier

train

public void train(DataSet trainingData,
                  DataSet tuneData)
           throws java.lang.Exception

getAccuracy

public double getAccuracy(double[][] testdata,
                          int[] exp)

train

public void train(DataSet trainingData)
           throws java.lang.Exception

train() : randomly pick 10% of trainingdata for tune set.

Overrides:

train in class Classifier

reportAccuracies

public void reportAccuracies(int epoch,
                             DataSet train,
                             DataSet tune)

runEpoch

public void runEpoch(double[][] epoch_data,
                     double[][] exp)
              throws java.lang.Exception

trainExample

public void trainExample(double[] input,
                         double[] exp_output)

classify

public Feature classify(Example example)

Overrides:

classify in class Classifier

tune

public void tune(DataSet trainingData,
                 java.lang.Object[] parameters)

printClassifier

public java.lang.String printClassifier()

Overrides:

printClassifier in class Classifier

cloneClassifier

public Classifier cloneClassifier()

Overrides:

cloneClassifier in class Classifier

setParameter

public void setParameter(int i,
                         java.lang.Object parameter)

Overrides:

setParameter in class Classifier