weka.classifiers.rules
Class FURIA.NumericAntd

java.lang.Object
  weka.classifiers.rules.FURIA.NumericAntd

All Implemented Interfaces:

java.io.Serializable, Copyable, WeightedInstancesHandler

Enclosing class:

FURIA

public class FURIA.NumericAntd
extends java.lang.Object

The antecedent with numeric attribute

See Also:

Serialized Form

Field Summary

boolean	fuzzyYet A flag determining whether this antecedent was successfully fuzzified yet
double	splitPoint The split point for this numeric antecedent
double	supportBound The edge point for the fuzzy set of this numeric antecedent

Constructor Summary

FURIA.NumericAntd(Attribute a)
Constructor

Method Summary

java.lang.Object	copy() Implements Copyable
double	covers(Instance inst) The degree of coverage for the instance given that antecedent
double	getSplitPoint() Get split point of this numeric antecedent
Instances[]	splitData(Instances insts, double defAcRt, double cl) Implements the splitData function.
java.lang.String	toString() Prints this antecedent

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

splitPoint

public double splitPoint

The split point for this numeric antecedent

supportBound

public double supportBound

The edge point for the fuzzy set of this numeric antecedent

fuzzyYet

public boolean fuzzyYet

A flag determining whether this antecedent was successfully fuzzified yet

Constructor Detail

FURIA.NumericAntd

public FURIA.NumericAntd(Attribute a)

Constructor

Method Detail

getSplitPoint

public double getSplitPoint()

Get split point of this numeric antecedent

Returns:

the split point of this numeric antecedent

copy

public java.lang.Object copy()

Implements Copyable

Specified by:

copy in interface Copyable

Returns:

a copy of this object

splitData

public Instances[] splitData(Instances insts,
                             double defAcRt,
                             double cl)

Implements the splitData function. This procedure is to split the data into two bags according to the information gain of the numeric attribute value The maximum infoGain is also calculated.

Parameters:

insts - the data to be split

defAcRt - the default accuracy rate for data

cl - the class label to be predicted

Returns:

the array of data after split

covers

public double covers(Instance inst)

The degree of coverage for the instance given that antecedent

Parameters:

inst - the instance in question

Returns:

the numeric value indicating the membership of the instance for this antecedent

toString

public java.lang.String toString()

Prints this antecedent

Returns:

a textual description of this antecedent