R: Transforming from crisp set into linguistic terms

fuzzifier {frbs}

R Documentation

Transforming from crisp set into linguistic terms

Description

Fuzzification refers to the process of transforming a crisp set into linguistic terms.

Usage

fuzzifier(data, num.varinput, num.labels.input, varinp.mf)

Arguments

`data`	a matrix of data containing numerical elements.
`num.varinput`	number of input variables.
`num.labels.input`	the number of labels of the input variables.
`varinp.mf`	a matrix containing the parameters to form the membership functions. See the Detail section.

Details

In this function, there are five shapes of membership functions implemented, namely TRIANGLE, TRAPEZOID, GAUSSIAN, SIGMOID, and BELL. They are represented by a matrix that the dimension is (5, n) where n is a multiplication the number of linguistic terms/labels and the number of input variables. The rows of the matrix represent: The first row is the type of membership function, where 1 means TRIANGLE, 2 means TRAPEZOID in left side, 3 means TRAPEZOID in right side, 4 means TRAPEZOID in the middle, 5 means GAUSSIAN, 6 means SIGMOID, and 7 means BELL. And, the second up to fifth row indicate the corner points to construct the functions.

TRIANGLE has three parameters (a, b, c), where b is the center point of the TRIANGLE, and a and c are the left and right points, respectively.
TRAPEZOID has four parameters (a, b, c, d).
GAUSSIAN has two parameters (mean and variance).
SIGMOID has two parameters (\gamma and c) for representing steepness of the function and distance from the origin, respectively.
BELL has three parameters (a, b, c).

For example:

varinp.mf <- matrix(c(2,1,3,2,3,0,30,60,0,40,20,50,80,

30,80,40,70,100,60,100,0,0,100,0,100), nrow=5, byrow=TRUE)

Value