keel.Algorithms.Instance_Generation.BasicMethods

Class ARS

java.lang.Object

keel.Algorithms.Instance_Generation.Basic.PrototypeGenerator

keel.Algorithms.Instance_Generation.BasicMethods.RandomSelector

keel.Algorithms.Instance_Generation.BasicMethods.ARS

public class ARS
extends RandomSelector

Implements a random selector but taking proportional number of prototypes in order to their occurences (that is, their a priory probabilities).

Author:

diegoj

Field Summary

Fields inherited from class keel.Algorithms.Instance_Generation.BasicMethods.RandomSelector

numberOfPrototypesSelected

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

algorithmName, generatedDataSet, SEED, seedDefaultValueList, trainingDataSet

Constructor Summary

Constructors

Constructor and Description
ARS(PrototypeSet t, int n) Creates a new AdvanceRandomSelector
ARS(PrototypeSet t, Parameters params) Creates a new AdvanceRandomSelector

Method Summary

Modifier and Type	Method and Description
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
PrototypeSet	reduceSet() Extract prototypes from the training data and returns them in a new data set.

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

ARS

public ARS(PrototypeSet t,
           int n)

Creates a new AdvanceRandomSelector

Parameters:

t - Traning data set

n - Number of prototypes to be extracted.

ARS

public ARS(PrototypeSet t,
           Parameters params)

Creates a new AdvanceRandomSelector

Parameters:

t - Traning data set

params - External parameters

Method Detail

reduceSet

public PrototypeSet reduceSet()

Extract prototypes from the training data and returns them in a new data set.

Overrides:

reduceSet in class RandomSelector

Returns:

PrototypeSet containing the extracted 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 will contain the test data set

Parameters:

args - Arguments of the main function.