keel.Algorithms.Discretizers.ExtendedChi2_Discretizer

Class ExtendedChi2Discretizer

java.lang.Object

keel.Algorithms.Discretizers.ExtendedChi2_Discretizer.Discretizer

keel.Algorithms.Discretizers.ExtendedChi2_Discretizer.ExtendedChi2Discretizer

public class ExtendedChi2Discretizer
extends Discretizer

This class implements the Chi2 discretizer.

Since:

JDK1.5

Version:

1.0

Author:

Written by Salvador García (University of Jaén - Jaén) 3/04/2009

Field Summary

Fields inherited from class keel.Algorithms.Discretizers.ExtendedChi2_Discretizer.Discretizer

classOfInstances, cutPoints, cutPointsTMP, inconsistencyThreshold, realAttributes, realValues

Constructor Summary

Constructors

Constructor and Description
ExtendedChi2Discretizer() Default constructor.

Method Summary

Modifier and Type	Method and Description
protected java.util.Vector	discretizeAttribute(int attribute, int[] values, java.util.Vector<Interval> intervals, double levelSig) This abstract method creates the cut points of the attribute given using its values for each instances given.
protected java.util.Vector	discretizeAttributePreliminary(int attribute, int[] values, java.util.Vector<Interval> intervals) This abstract method creates a preliminary cut points of the attribute given using its values for each instances given without sigma level.
protected java.util.Vector<Interval>	obtainIntervals(int attribute, int[] values, int begin, int end) Returns the discretized intervals of the given attribute.

Methods inherited from class keel.Algorithms.Discretizers.ExtendedChi2_Discretizer.Discretizer

applyDiscretization, buildCutPoints, discretize, discretizeTMP, getCutPoint, getNumIntervals, inconsistencyCheck, sortValues

Methods inherited from class java.lang.Object

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

Constructor Detail

ExtendedChi2Discretizer

public ExtendedChi2Discretizer()

Default constructor.

Method Detail

obtainIntervals

protected java.util.Vector<Interval> obtainIntervals(int attribute,
                                                     int[] values,
                                                     int begin,
                                                     int end)

Description copied from class: Discretizer

Returns the discretized intervals of the given attribute.

Specified by:

obtainIntervals in class Discretizer

Parameters:

attribute - given attribute to discretize.

values - given attribute values in the dataset.

begin - First position of the section to discretize.

end - Last position of the section to discretize.

Returns:

the discretized intervals of the given attribute.

discretizeAttributePreliminary

protected java.util.Vector discretizeAttributePreliminary(int attribute,
                                                          int[] values,
                                                          java.util.Vector<Interval> intervals)

Description copied from class: Discretizer

This abstract method creates a preliminary cut points of the attribute given using its values for each instances given without sigma level. Every Chi discretizer should implement this method with its particular scheme.

Specified by:

discretizeAttributePreliminary in class Discretizer

Parameters:

attribute - given attribute to discretize.

values - given attribute values in the dataset.

intervals - given intervals.

Returns:

the cut points of the attribute given

discretizeAttribute

protected java.util.Vector discretizeAttribute(int attribute,
                                               int[] values,
                                               java.util.Vector<Interval> intervals,
                                               double levelSig)

Description copied from class: Discretizer

This abstract method creates the cut points of the attribute given using its values for each instances given. Every Chi discretizer should implement this method with its particular scheme.

Specified by:

discretizeAttribute in class Discretizer

Parameters:

attribute - given attribute to discretize.

values - given attribute values in the dataset.

intervals - given intervals.

levelSig - Sigma level.

Returns:

the cut points of the attribute given