keel.Algorithms.Instance_Generation.PNN

Class PNNGenerator

java.lang.Object

keel.Algorithms.Instance_Generation.Basic.PrototypeGenerator

keel.Algorithms.Instance_Generation.PNN.PNNGenerator

Direct Known Subclasses:

MCAGenerator

public class PNNGenerator
extends PrototypeGenerator

Prototypes for Nearest Neighbor Classifiers

Author:

diegoj

Field Summary

Fields

Modifier and Type	Field and Description
protected int	numberOfPrototypes Number of prototypes to be generated.
protected boolean	useNumberOfPrototypes Informs if the algorithm must generate a specified number of prototypes.

Fields inherited from class keel.Algorithms.Instance_Generation.Basic.PrototypeGenerator

algorithmName, generatedDataSet, SEED, seedDefaultValueList, trainingDataSet

Constructor Summary

Constructors

Constructor and Description
PNNGenerator(PrototypeSet tSet) Build a new algorithm PNNGenerator that will reduce a prototype set.
PNNGenerator(PrototypeSet tSet, double percentageOfPrototypes) Build a new algorithm PNNGenerator that will reduce a prototype set.
PNNGenerator(PrototypeSet tSet, int numberOfProts) Build a new algorithm PNNGenerator that will reduce a prototype set.
PNNGenerator(PrototypeSet _trainingDataSet, Parameters parameters) Build a new algorithm PNNGenerator that will reduce a prototype set.

Method Summary

Modifier and Type	Method and Description
protected PrototypeSet	controlledReduction() Performs a reduction of the training data set by the PNNGenerator (aka Chang) method.
static void	main(java.lang.String[] args) General main for all the prototoype generators Arguments: 0: Filename with the training data set to be condensed. 1: Filename wich contains the test data set. 3: Seed of the Random Number Generator. 4: number of prototypes to be generated (OPTIONAL)
protected PrototypeSet	maximumReduction() Performs the maximum reduction of the training data set by the PNNGenerator (aka Chang) method.
protected Pair<Prototype,Prototype>	nearestPrototypesIn(PrototypeSet A, PrototypeSet B, MatrixOfDistances m) Returns the two nearest prototypes in two different sets.
PrototypeSet	reduceSet() Performs a reduction of the training data set by the PNNGenerator (aka Chang) method.

Methods inherited from class keel.Algorithms.Instance_Generation.Basic.PrototypeGenerator

absoluteAccuracy, absoluteAccuracyAndError, absoluteAccuracyKNN, accuracy, accuracy2, desordenar_vector_sin, desordenar_vector, execute, generateReducedDataSet, getResultingAccuracy, getResultingAccuracy, getResults, getResultsOfAccuracy, getResultsOfAccuracy, getSeed, getSetSizeFromPercentage, getSetSizeFromPercentage, getTime, inic_vector_sin, inic_vector, saveResultsOfAccuracyIn, saveResultsOfAccuracyIn, selecRandomSet, setSeed, showResultsOfAccuracy, showResultsOfAccuracy

Methods inherited from class java.lang.Object

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

Field Detail

useNumberOfPrototypes

protected boolean useNumberOfPrototypes

Informs if the algorithm must generate a specified number of prototypes.

numberOfPrototypes

protected int numberOfPrototypes

Number of prototypes to be generated.

Constructor Detail

PNNGenerator

public PNNGenerator(PrototypeSet tSet)

Build a new algorithm PNNGenerator that will reduce a prototype set.

Parameters:

tSet - Traning data set to be reduced.

PNNGenerator

public PNNGenerator(PrototypeSet tSet,
                    int numberOfProts)

Build a new algorithm PNNGenerator that will reduce a prototype set.

Parameters:

tSet - Traning data set to be reduced.

numberOfProts - Number of prototypes to be generated.

PNNGenerator

public PNNGenerator(PrototypeSet tSet,
                    double percentageOfPrototypes)

Build a new algorithm PNNGenerator that will reduce a prototype set.

Parameters:

tSet - Traning data set to be reduced.

percentageOfPrototypes - Percentage of prototypes of training to be generated.

PNNGenerator

public PNNGenerator(PrototypeSet _trainingDataSet,
                    Parameters parameters)

Build a new algorithm PNNGenerator that will reduce a prototype set.

Parameters:

_trainingDataSet - training datast.

parameters - Parameters needed for the algoritm, in this case, random seedDefaultValueList only.

Method Detail

nearestPrototypesIn

protected Pair<Prototype,Prototype> nearestPrototypesIn(PrototypeSet A,
                                                        PrototypeSet B,
                                                        MatrixOfDistances m)

Returns the two nearest prototypes in two different sets.

Parameters:

A - Set which first prototype belongs to.

B - Set which second prototype belongs to.

m - matrix of distances.

Returns:

A pair which elements are the nearest prototypes in A and B (first and second, resp.).

maximumReduction

protected PrototypeSet maximumReduction()

Performs the maximum reduction of the training data set by the PNNGenerator (aka Chang) method.

Returns:

Reduced prototype set by Chang's method.

controlledReduction

protected PrototypeSet controlledReduction()

Performs a reduction of the training data set by the PNNGenerator (aka Chang) method. Stopped by reaching a specified number of prototypes.

Returns:

Reduced prototype set by Chang's method limited by the number of prototypes.

reduceSet

public PrototypeSet reduceSet()

Performs a reduction of the training data set by the PNNGenerator (aka Chang) method. It can use early stopping of the method.

Overrides:

reduceSet in class PrototypeGenerator

Returns:

Reduced prototype set by Chang's method limited by the number of prototypes.

main

public static void main(java.lang.String[] args)

General main for all the prototoype generators Arguments: 0: Filename with the training data set to be condensed. 1: Filename wich contains the test data set. 3: Seed of the Random Number Generator. 4: number of prototypes to be generated (OPTIONAL)

Parameters:

args - Arguments of the main function.