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anfis (version 0.99.1)

Adaptive Neuro Fuzzy Inference System in R

Description

The package implements ANFIS Type 3 Takagi and Sugeno's fuzzy if-then rule network with the following features: (1) Independent number of membership functions(MF) for each input, and also different MF extensible types. (2) Type 3 Takagi and Sugeno's fuzzy if-then rule (3) Full Rule combinations, e.g. 2 inputs 2 membership funtions -> 4 fuzzy rules (4) Hibrid learning, i.e. Descent Gradient for precedents and Least Squares Estimation for consequents (5) Multiple outputs.

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Version

Install

install.packages('anfis')

Monthly Downloads

3

Version

0.99.1

License

GPL (>= 2)

Maintainer

Cristobal Fresno

Last Published

January 16th, 2015

Functions in anfis (0.99.1)

plot

Plot ANFIS training errors
predict

Predict ANFIS' network output
plotMF

PlotMF/s ANFIS' MembershipFunction domain/s
extract-methods

Modify membership function parameters
fitted

ANFIS training results
getRules

Getters for ANFIS object
print,MembershipFunction-method

Print a MembershipFunction object
evaluateMF

evaluateMF evaluate membership
trainSet

Bidimentional Sinc train set example
print

Print and Show an ANFIS object
ANFIS-class

ANFIS S4 class implementation in R
MembershipFunction-class

MembershipFunction S4 class
initialize

initialize ANFIS object constructor
derivateMF

derivateMF derivate membership function
show,MembershipFunction-method

Show a MembershipFunction object
BellMF-class

Bell Membership Function S4 class
Anfis-package

Adaptive Neuro Fuzzy Inference System in R
anfis3

Anfis' trained example to use for demonstration
GaussianMF-class

GaussianMF Membership Function S4 class
LSE

Train ANFIS network
NormalizedGaussianMF-class

NormalizedGaussianMF Membership Function S4 class