LkbConfidenceSupportL {FKBL}R Documentation

Creates a knowledge base

Description

This is the implementation of confidence and support method. Similar to LkbConfidenceSupport. It needs the LkbConfidenceSupporP. It is based in exploring every rule possibility, and test its confidence and its support. Support is a concept related with the amount of points covered by the rule. Confidence is related with the predominant class in the area covered by the rule. Only rules with any amount of support are included. The inferred class of a rule is set so the confidence is maximized. There is a weight associated with a rule, and there are 4 different heuristic methods to obtain it, plus a fifth method which simply states an standard value of $frac{1}{2} $. Described in chapter 2, pages 018-025 at Ishibuchi et al.\

Usage

 LkbConfidenceSupportL(lis,train)

Arguments

Takes the list of parameters and the train dataset.

lis A list with the arguments of the function. It is created with LkbConfidenceSupportP.
train The train dataset.

Value

Returns a knowledge base with the partitions and the rules.

Source

begin{itemize}

  • Ishibuchi, H., Nakashima, T., Nii, M.
  • "Classification and modeling with linguistic information granules."
  • Soft Computing Approaches to Linguistic Data Mining.
  • Springer-Verlag, 2003 end{itemize}

    Examples

     data(P)
     Params<-LkbConfidenceSupportP(P,0)
     data(trainA)
     LkbConfidenceSupportL(Params,trainA)
    

    [Package FKBL version 0.50-4 Index]