keel.Algorithms.Instance_Generation.LVQ

Class LVQ2_1

java.lang.Object

keel.Algorithms.Instance_Generation.Basic.PrototypeGenerator

keel.Algorithms.Instance_Generation.LVQ.LVQGenerator

keel.Algorithms.Instance_Generation.LVQ.LVQ1

keel.Algorithms.Instance_Generation.LVQ.LVQ2

keel.Algorithms.Instance_Generation.LVQ.LVQ2_1

public class LVQ2_1
extends LVQ2

LVQ2.1 algorithm

Author:

diegoj

Field Summary

Fields inherited from class keel.Algorithms.Instance_Generation.LVQ.LVQ2

DEFAULT_WINDOW_WIDTH, windowLowerBound, windowWidth

Fields inherited from class keel.Algorithms.Instance_Generation.LVQ.LVQ1

alpha_0, ALPHA_DEFAULT_VALUE, chosenRandomIndex, IALPHA, randomIndexes

Fields inherited from class keel.Algorithms.Instance_Generation.LVQ.LVQGenerator

initial, initialset, iterations, numberOfPrototypesGenerated

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

algorithmName, generatedDataSet, SEED, seedDefaultValueList, trainingDataSet

Constructor Summary

Constructors

Constructor and Description
LVQ2_1(PrototypeSet T, int iterations, double pcNprot, double alpha_0, double windowWidth) Construct an LVQ2.1 algorithm.
LVQ2_1(PrototypeSet T, int iterations, int n_prot, double alpha_0, double windowWidth) Construct an LVQ2.1 algorithm.
LVQ2_1(PrototypeSet T, Parameters parameters) Construct an LVQ2.1 algorithm.

Method Summary

Modifier and Type	Method and Description
protected void	correct(Prototype i, PrototypeSet tData) Corrects a prototype of a set.
protected void	hardCorrect(Prototype i, PrototypeSet tData) Corrects a prototype of a set.
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 will contain the test data set 3: k Number of neighbors used in the KNN function

Methods inherited from class keel.Algorithms.Instance_Generation.LVQ.LVQ1

extract, initDataSet, initDataSetRandomMode, penalize, reward

Methods inherited from class keel.Algorithms.Instance_Generation.LVQ.LVQGenerator

reduceSet

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

Constructor Detail

LVQ2_1

public LVQ2_1(PrototypeSet T,
              int iterations,
              int n_prot,
              double alpha_0,
              double windowWidth)

Construct an LVQ2.1 algorithm.

Parameters:

T - training data set.

iterations - Number of iterations to be performed.

n_prot - Number of prototypes to be returned.

alpha_0 - Alpha constant of the algorithm.

windowWidth - Window width parameter.

LVQ2_1

public LVQ2_1(PrototypeSet T,
              int iterations,
              double pcNprot,
              double alpha_0,
              double windowWidth)

Construct an LVQ2.1 algorithm.

Parameters:

T - training data set.

iterations - Number of iterations to be performed.

pcNprot - Size of reduced set as percentage of training size.

alpha_0 - Alpha constant of the algorithm.

windowWidth - Window width parameter.

LVQ2_1

public LVQ2_1(PrototypeSet T,
              Parameters parameters)

Construct an LVQ2.1 algorithm.

Parameters:

T - training data set.

parameters - Parameters of the algorithms.

Method Detail

hardCorrect

protected void hardCorrect(Prototype i,
                           PrototypeSet tData)

Corrects a prototype of a set. Non-Kohonen method.

Parameters:

i - Prototype whose nearest-neighbors of same and different class will be modified.

tData - Data set in which KNN operation will be performed.

correct

protected void correct(Prototype i,
                       PrototypeSet tData)

Corrects a prototype of a set.

Overrides:

correct in class LVQ2

Parameters:

i - Prototype whose nearest-neighbors of same and different class will be modified.

tData - Data set in which KNN operation will be performed.

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 will contain the test data set 3: k Number of neighbors used in the KNN function

Parameters:

args - Arguments of the main function.