keel.Algorithms.Instance_Generation.SSMASFLSDE

Class SSMASFLSDE

java.lang.Object

keel.Algorithms.Preprocess.Basic.Metodo

keel.Algorithms.Instance_Generation.SSMASFLSDE.SSMASFLSDE

public class SSMASFLSDE
extends Metodo

Field Summary

Fields

Modifier and Type	Field and Description
protected int	numberOfClass
protected int	numberOfPrototypes
protected int	numberOfStrategies
java.lang.String	Script

Fields inherited from class keel.Algorithms.Preprocess.Basic.Metodo

clasesTest, clasesTrain, datosTest, datosTrain, distanceEu, entradas, ficheroSalida, ficheroTest, ficheroTraining, ficheroValidation, nEntradas, nominalDistance, nominalTrain, nulosTrain, realTest, realTrain, relation, salida, stdDev, test, training

Constructor Summary

Constructors

Constructor and Description
SSMASFLSDE(java.lang.String ficheroScript)
SSMASFLSDE(java.lang.String ficheroScript, InstanceSet train)

Method Summary

Modifier and Type	Method and Description
static Prototype	_1nn(Prototype current, PrototypeSet dataSet) Implements the 1NN algorithm
double	classficationAccuracy1NN(PrototypeSet training, PrototypeSet test)
void	desordenar_vector_sin(int[] vector)
protected static double	distance(double[] instance1, double[] instance2) Calculates the Euclidean distance between two instances
protected static double	distanceWeighting(double[] instance1, double[] instance2, double[] Weights) Calculates the Euclidean distance between two instances
void	ejecutar()
void	establishTrain(PrototypeSet trainPG)
static int	evaluate(double[] example, double[][] trainData, int nClasses, int[] trainOutput, int k) Evaluates a instance to predict its class.
void	inic_vector_sin(int[] vector, int without)
void	leerConfiguracion(java.lang.String ficheroScript) Reads the parameters of the algorithm.
double	lsff(double Fi, double CRi, PrototypeSet[] population, int actual, int mejor) Local Search Fitness Function
PrototypeSet	mutant(PrototypeSet[] population, int actual, int mejor, double SFi)
static PrototypeSet	readPrototypeSet(java.lang.String nameOfFile) Reads the prototype set from a data file.
static PrototypeSet	readPrototypeSet2(InstanceSet training)
PrototypeSet	reduceSet(PrototypeSet initial) Generate a reduced prototype set by the SADEGenerator method.
PrototypeSet	SFGSS(PrototypeSet[] population, int actual, int mejor, double CRi) SFGSS local Search.
PrototypeSet	SFHC(PrototypeSet[] population, int actual, int mejor, double SFi, double CRi) SFHC local search
static void	writeOutput(java.lang.String filename, int[][] realClass, int[][] prediction, Attribute[] inputs, Attribute output, java.lang.String relation) Prints output files.

Methods inherited from class keel.Algorithms.Preprocess.Basic.Metodo

normalizar

Methods inherited from class java.lang.Object

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

Field Detail

Script

public java.lang.String Script

numberOfClass

protected int numberOfClass

numberOfPrototypes

protected int numberOfPrototypes

numberOfStrategies

protected int numberOfStrategies

Constructor Detail

SSMASFLSDE

public SSMASFLSDE(java.lang.String ficheroScript)

SSMASFLSDE

public SSMASFLSDE(java.lang.String ficheroScript,
                  InstanceSet train)

Method Detail

establishTrain

public void establishTrain(PrototypeSet trainPG)

readPrototypeSet

public static PrototypeSet readPrototypeSet(java.lang.String nameOfFile)

Reads the prototype set from a data file.

Parameters:

nameOfFile - Name of data file to be read.

Returns:

PrototypeSet built with the data of the file.

readPrototypeSet2

public static PrototypeSet readPrototypeSet2(InstanceSet training)

inic_vector_sin

public void inic_vector_sin(int[] vector,
                            int without)

desordenar_vector_sin

public void desordenar_vector_sin(int[] vector)

mutant

public PrototypeSet mutant(PrototypeSet[] population,
                           int actual,
                           int mejor,
                           double SFi)

lsff

public double lsff(double Fi,
                   double CRi,
                   PrototypeSet[] population,
                   int actual,
                   int mejor)

Local Search Fitness Function

Parameters:

Fi -

xt -

xr -

xs -

actual -

SFGSS

public PrototypeSet SFGSS(PrototypeSet[] population,
                          int actual,
                          int mejor,
                          double CRi)

SFGSS local Search.

Parameters:

population -

Returns:

SFHC

public PrototypeSet SFHC(PrototypeSet[] population,
                         int actual,
                         int mejor,
                         double SFi,
                         double CRi)

SFHC local search

Parameters:

xt -

xr -

xs -

actual -

SFi -

Returns:

_1nn

public static Prototype _1nn(Prototype current,
                             PrototypeSet dataSet)

Implements the 1NN algorithm

Parameters:

current - Prototype which the algorithm will find its nearest-neighbor.

dataSet - Prototype set in which the algorithm will search.

Returns:

Nearest prototype to current in the prototype set dataset.

classficationAccuracy1NN

public double classficationAccuracy1NN(PrototypeSet training,
                                       PrototypeSet test)

reduceSet

public PrototypeSet reduceSet(PrototypeSet initial)

Generate a reduced prototype set by the SADEGenerator method.

Returns:

Reduced set by SADEGenerator's method.

ejecutar

public void ejecutar()

writeOutput

public static void writeOutput(java.lang.String filename,
                               int[][] realClass,
                               int[][] prediction,
                               Attribute[] inputs,
                               Attribute output,
                               java.lang.String relation)

Prints output files.

Parameters:

filename - Name of output file

realClass - Real output of instances

prediction - Predicted output for instances

distance

protected static double distance(double[] instance1,
                                 double[] instance2)

Calculates the Euclidean distance between two instances

Parameters:

instance1 - First instance

instance2 - Second instance

Returns:

The Euclidean distance

distanceWeighting

protected static double distanceWeighting(double[] instance1,
                                          double[] instance2,
                                          double[] Weights)

Calculates the Euclidean distance between two instances

Parameters:

instance1 - First instance

instance2 - Second instance

Returns:

The Euclidean distance

evaluate

public static int evaluate(double[] example,
                           double[][] trainData,
                           int nClasses,
                           int[] trainOutput,
                           int k)

Evaluates a instance to predict its class.

Parameters:

example - Instance evaluated

Returns:

Class predicted

leerConfiguracion

public void leerConfiguracion(java.lang.String ficheroScript)

Description copied from class: Metodo

Reads the parameters of the algorithm. Must be implemented in the subclass.

Overrides:

leerConfiguracion in class Metodo

Parameters:

ficheroScript - Configuration script