TkbAnalytic {FKBL}R Documentation

Analytic algorithm. Tweaks a kB

Description

This algorithm is called Analytic. It is the same as TkbAnalyticL, but it has not the parameters packed in a list. It takes a knowledge base and tweaks its weights to fit better a given train data. It is based in the idea of checking every training case, and for the cases whose class wasn't correctly inferred, it tries to improve the rule set. This improvement is done by examining three different solutions. First, lowering the winning rule's weight so it is no longer the winning rule in this situation. Second, find a non winning rule which wouldn't have made a mistake, and rise its weight up to the value which makes it to win. Third, leave it as is. The situation which gives less error with the whole training set, would be the chosen one. This algorithm is described in chapter 3, pages 048-057 at Ishibuchi et al.\

Usage

 TkbAnalytic(kB, itera, e, train)

Arguments

Takes knowledge base, the maximum number of iterations, the e and the train data.

kB The knowledge base to tweak.
itera The maximum number of iterations.
e The e parameter for analytic.
train The train data.

Value

Returns the tweaked knowledge base.

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(kB)
     data(trainA)
     TkbAnalytic(kB, 1000, 0.1, trainA)
    

    [Package FKBL version 0.50-4 Index]