org.gcube.dataanalysis.ecoengine.models.cores.neuralnetworks
Class Neural_Network

java.lang.Object
  extended by org.gcube.dataanalysis.ecoengine.models.cores.neuralnetworks.Neural_Network
All Implemented Interfaces:
Serializable

public class Neural_Network
extends Object
implements Serializable

See Also:
Serialized Form

Nested Class Summary
static class Neural_Network.ACTIVATIONFUNCTION
           
 
Field Summary
 double en
           
 Neuron[][] griglia
           
 double maxfactor
           
 double minfactor
           
 float status
           
 
Constructor Summary
Neural_Network(int N, int M, int attifun)
           
Neural_Network(int N, int M, int[] t, int attifun)
           
Neural_Network(int N, int M, int[] t, Neural_Network.ACTIVATIONFUNCTION attifun)
           
Neural_Network(int N, int M, int attifun, float[] V)
           
Neural_Network(int N, int M, Neural_Network.ACTIVATIONFUNCTION attifun)
           
Neural_Network(int N, int M, Neural_Network.ACTIVATIONFUNCTION attifun, float[] V)
           
 
Method Summary
static String generateNNName(String referenceEntity, String username, String neuralNetName)
           
 double[] getClassification(double[] out)
           
 double getCorrectValueForOutput(double output)
           
 double getCorrectValueFromOutput(double prob)
           
 double[] getNegativeCase()
           
 int getNumberOfInputs()
           
 int getNumberOfOutputs()
           
 double[] getPositiveCase()
           
static Neural_Network loadNN(String nomeFile)
           
static void main(String[] args)
           
static double[] preprocessObjects(double[] vector)
           
static double[] preprocessObjects(Object[] vector)
           
 double[] propagate(double[] input)
           
 void setAcceptanceThreshold(double treshold)
           
 void setCycles(double cycs)
           
 void setThreshold(double soglia)
           
static int[] setupInnerLayers(int... numberOfNeurons)
           
 void train(double[][] inputvet, double[][] correctoutputvet)
           
 void writeout(double numero, double soglia)
           
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Field Detail

griglia

public Neuron[][] griglia

maxfactor

public double maxfactor

minfactor

public double minfactor

status

public float status

en

public double en
Constructor Detail

Neural_Network

public Neural_Network(int N,
                      int M,
                      Neural_Network.ACTIVATIONFUNCTION attifun)

Neural_Network

public Neural_Network(int N,
                      int M,
                      Neural_Network.ACTIVATIONFUNCTION attifun,
                      float[] V)

Neural_Network

public Neural_Network(int N,
                      int M,
                      int[] t,
                      Neural_Network.ACTIVATIONFUNCTION attifun)

Neural_Network

public Neural_Network(int N,
                      int M,
                      int attifun)

Neural_Network

public Neural_Network(int N,
                      int M,
                      int attifun,
                      float[] V)

Neural_Network

public Neural_Network(int N,
                      int M,
                      int[] t,
                      int attifun)
Method Detail

setThreshold

public void setThreshold(double soglia)

getCorrectValueFromOutput

public double getCorrectValueFromOutput(double prob)

getCorrectValueForOutput

public double getCorrectValueForOutput(double output)

setAcceptanceThreshold

public void setAcceptanceThreshold(double treshold)

setCycles

public void setCycles(double cycs)

preprocessObjects

public static double[] preprocessObjects(Object[] vector)

preprocessObjects

public static double[] preprocessObjects(double[] vector)

getNumberOfOutputs

public int getNumberOfOutputs()

getNumberOfInputs

public int getNumberOfInputs()

getPositiveCase

public double[] getPositiveCase()

getNegativeCase

public double[] getNegativeCase()

setupInnerLayers

public static int[] setupInnerLayers(int... numberOfNeurons)

propagate

public double[] propagate(double[] input)

train

public void train(double[][] inputvet,
                  double[][] correctoutputvet)

writeout

public void writeout(double numero,
                     double soglia)

getClassification

public double[] getClassification(double[] out)

loadNN

public static Neural_Network loadNN(String nomeFile)

generateNNName

public static String generateNNName(String referenceEntity,
                                    String username,
                                    String neuralNetName)

main

public static void main(String[] args)


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