TkbAnalyticL {FKBL} | R Documentation |
This algorithm is called Analytic. It is the same as TkbAnalytic, but with the parameters packed in a list. It needs the TkbAnalyticP function to create the list of parameters. 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.\
TkbAnalyticL(lis,train)
Takes the list of parameters and the train data.
lis |
A list with the arguments of the function. It is created with TkbAnaliticP. |
train |
The train data. |
Returns the tweaked knowledge base.
begin{itemize}
data(kB) Params<-TkbAnalyticP(kB, 1000, 0.1) data(trainA) TkbAnalyticL(Params, trainA)