weka.classifiers.rules
Class ConjunctiveRule.Antd

java.lang.Object
  weka.classifiers.rules.ConjunctiveRule.Antd

All Implemented Interfaces:

java.io.Serializable

Direct Known Subclasses:

ConjunctiveRule.NominalAntd, ConjunctiveRule.NumericAntd

Enclosing class:

ConjunctiveRule

private abstract class ConjunctiveRule.Antd

extends java.lang.Object

implements java.io.Serializable

The single antecedent in the rule, which is composed of an attribute and the corresponding value. There are two inherited classes, namely NumericAntd and NominalAntd in which the attributes are numeric and nominal respectively.

Field Summary

protected Attribute	att The attribute of the antecedent
protected double	inform The information of this antecedent test on the growing data
protected double	maxInfoGain The maximum infoGain achieved by this antecedent test
protected double[]	uncover The parameters related to the data not covered by the previous antecedents when the class is nominal
protected double	uncoverSum The parameter related to the meanSquaredError of the data not covered by the previous antecedents when the class is numeric
protected double	uncoverWtSq The parameter related to the meanSquaredError of the data not covered by the previous antecedents when the class is numeric
protected double	uncoverWtVl The parameter related to the meanSquaredError of the data not covered by the previous antecedents when the class is numeric
protected double	value The attribute value of the antecedent.

Constructor Summary

ConjunctiveRule.Antd(Attribute a, double[] unc)
Constructor for nominal class

ConjunctiveRule.Antd(Attribute a, double uncoveredWtSq, double uncoveredWtVl, double uncoveredWts)

Method Summary

protected double	entropy(double[] value, double sum) Function used to calculate the entropy of given vector of values entropy = (1/sum)*{-sigma[i=1..P](Xi*log2(Xi)) + sum*log2(sum)} where P is the length of the vector
Attribute	getAttr()
double	getAttrValue()
double	getInfo()
double	getMaxInfoGain()
abstract boolean	isCover(Instance inst)
abstract Instances[]	splitData(Instances data, double defInfo)
abstract java.lang.String	toString()
protected double	wtMeanSqErr(double weightedSq, double weightedValue, double sum) Function used to calculate the weighted mean squared error, i.e., sum[x-avg(x)]^2 based on the given elements of the formula: meanSquaredError = sum(Wi*Xi^2) - (sum(WiXi))^2/sum(Wi)

Methods inherited from class java.lang.Object

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

Field Detail

att

protected Attribute att

The attribute of the antecedent

value

protected double value

The attribute value of the antecedent. For numeric attribute, value is either 0(1st bag) or 1(2nd bag)

maxInfoGain

protected double maxInfoGain

The maximum infoGain achieved by this antecedent test

inform

protected double inform

The information of this antecedent test on the growing data

uncoverWtSq

protected double uncoverWtSq

The parameter related to the meanSquaredError of the data not covered by the previous antecedents when the class is numeric

uncoverWtVl

protected double uncoverWtVl

The parameter related to the meanSquaredError of the data not covered by the previous antecedents when the class is numeric

uncoverSum

protected double uncoverSum

The parameter related to the meanSquaredError of the data not covered by the previous antecedents when the class is numeric

uncover

protected double[] uncover

The parameters related to the data not covered by the previous antecedents when the class is nominal

Constructor Detail

ConjunctiveRule.Antd

public ConjunctiveRule.Antd(Attribute a,
                            double[] unc)

Constructor for nominal class

ConjunctiveRule.Antd

public ConjunctiveRule.Antd(Attribute a,
                            double uncoveredWtSq,
                            double uncoveredWtVl,
                            double uncoveredWts)

Method Detail

splitData

public abstract Instances[] splitData(Instances data,
                                      double defInfo)

isCover

public abstract boolean isCover(Instance inst)

toString

public abstract java.lang.String toString()

getAttr

public Attribute getAttr()

getAttrValue

public double getAttrValue()

getMaxInfoGain

public double getMaxInfoGain()

getInfo

public double getInfo()

wtMeanSqErr

protected double wtMeanSqErr(double weightedSq,
                             double weightedValue,
                             double sum)

Function used to calculate the weighted mean squared error, i.e., sum[x-avg(x)]^2 based on the given elements of the formula: meanSquaredError = sum(Wi*Xi^2) - (sum(WiXi))^2/sum(Wi)

Parameters:

weightedSq - sum(Wi*Xi^2)

weightedValue - sum(WiXi)

sum - sum of weights

Returns:

the weighted mean-squared error

entropy

protected double entropy(double[] value,
                         double sum)

Function used to calculate the entropy of given vector of values entropy = (1/sum)*{-sigma[i=1..P](Xi*log2(Xi)) + sum*log2(sum)} where P is the length of the vector

Parameters:

value - the given vector of values

sum - the sum of the given values. It's provided just for efficiency.

Returns:

the entropy