simC {ipsfs}

IFS similarity measure simC

Description

IFS similarity measure values using simC computation technique with membership, and non-membership values of two objects or set of objects.

Usage

simC(ma, na, mb, nb, k)

Arguments

ma

IFS membership values for the data set x computed using either triangular or trapezoidal or guassian membership function

na

IFS non-membership values for the data set x computed using either Sugeno and Terano's or Yager's non-membership function

mb

IFS membership values for the data set y computed using either triangular or trapezoidal or guassian membership function

nb

IFS non-membership values for the data set y computed using either Sugeno and Terano's or Yager's non-membership function

k

A constant value, considered as 1

Value

The IFS similarity values of data set y with data set x

References

S.-M. Chen. Measures of similarity between vague sets. Fuzzy sets and Systems, 74(2):217 - 223, 1995.

Examples

x<-matrix(c(12,9,14,11,21,16,15,24,20,17,14,11),nrow=4)
y<-matrix(c(11,21,6),nrow=1)
a<-mn(x)
b<-std(x)
a1<-mn(y)
b1<-std(y)
lam<-0.5
ma<-memG(a,b,x)
na<-nonmemS(ma,lam)
mb<-memG(a1,b1,y)
nb<-nonmemS(mb,lam)
k<-1
simC(ma,na,mb,nb,k)
#[1] 0.7005061 0.7011282 0.8783314 0.8783314