NormalizedGaussianMF-class: NormalizedGaussianMF Membership Function S4 class

In anfis: Adaptive Neuro Fuzzy Inference System in R

Description

Represent a concrete NormalizedGaussianMF shaped [0,1] Membership Function S4 class with parameters mu, sigma. Slots inherited of MembershipFunction class and related functions: show, print, derivateMF, evaluateMF, [ and [<-.

Slots

parameters

named numeric vector with parameters of Membership Function.

nParameters

integer with the number of parameters for validity check.

name

character The description of the membership function.

expression

expression object just to display purposes.

Note

derivateMF, evaluateMF are extended. Prototype is defined and validity is inherited.

Author(s)

Cristobal Fresno [e-mail], Andrea S. Llera [e-mail] and Elmer A. Fernandez [e-mail]

See Also

BellMF-class and GaussianMF-class

Other Membership Functions: BellMF, BellMF-class; GaussianMF, GaussianMF-class; MembershipFunction, MembershipFunction-class; [,MembershipFunction-method, [<-,MembershipFunction-method, extract-methods, extract-methods; derivateMF, derivateMF, derivateMF, derivateMF, derivateMF, derivateMF,BellMF-method, derivateMF,GaussianMF-method, derivateMF,MembershipFunction-method, derivateMF,NormalizedGaussianMF-method, derivateMF-methods; evaluateMF, evaluateMF, evaluateMF, evaluateMF, evaluateMF, evaluateMF,BellMF-method, evaluateMF,GaussianMF-method, evaluateMF,MembershipFunction-method, evaluateMF,NormalizedGaussianMF-method, evaluateMF-methods; print,MembershipFunction-method; show,MembershipFunction-method

Examples

#NormalizedGaussianMF example I
#A normalized Gaussian membership function with default paramateres (mu=0, sigma=1)
#The derivate of the first parameter at x, should be 1
#The derivate of the first parameter at x, should be 0
#The derivate on "mu" parameter at x, should be 0
normalizedGaussian <- new(Class="NormalizedGaussianMF")
normalizedGaussian
evaluateMF(object=normalizedGaussian, x=0)
derivateMF(object=normalizedGaussian, x=0, i=1)
derivateMF(object=normalizedGaussian, x=0, i="mu")
#
#NormalizedGaussianMF example II
#A normalized Gaussian membership function with parameters (mu=0, sigma=1)
#The derivate of the first parameter at x, should be 1
#The derivate of the first parameter at x, should be 0
#The derivate on "mu" parameter at x, should be 0
normalizedGaussian2 <- new(Class="NormalizedGaussianMF",
 parameters=c(mu=0,sigma=1))
normalizedGaussian2
evaluateMF(object=normalizedGaussian2, x=0)
derivateMF(object=normalizedGaussian2, x=0, i=1)
derivateMF(object=normalizedGaussian2, x=0, i="mu")

anfis documentation built on May 2, 2019, 2:38 a.m.