Training Phase Of FLR

Share:

Description

Creates rules for classification using FLR.

Usage

1
2
3
4
5
6
7
  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.