trainNow: Training Phase Of FLR

In FLR: Fuzzy Logic Rule Classifier

Description

Creates rules for classification using FLR.

Usage

  trainNow(trainData,param,rhoa=0.5,l=6,x0=0.5,EPSILON=10^(-6))
  join(inpBuf,num)
  theta(x,x0,param)
  ufun(x,x0,l,param)
  valuation(fuzlat,x0,l,param)
  createNframe(trainData)
  createNlist(trainData)

Arguments

trainData	an input data.frame.
param	parameter indicating linear positive valuation for 0 and sigmoid positive valuation for 1. The default value is set to 0.
rhoa	vigilance parameter in range [0,1]. The default value is set to 0.6.
l	parameter of u and theta functions of FLR. The default value is set to 6.
x0	parameter of u and theta functions of FLR. The default value is set to 0.4.
EPSILON	parameter EPSILON.The default value is set to 10^(-6).
inpBuf	input buffer.
num	num
x	fuzzy lattice
fuzlat	fuzzy lattice

Value

return a data.frame of the learned code.

FLR documentation built on May 2, 2019, 3:43 p.m.