Package: frbs 3.2-0

Christoph Bergmeir

frbs: Fuzzy Rule-Based Systems for Classification and Regression Tasks

An implementation of various learning algorithms based on fuzzy rule-based systems (FRBSs) for dealing with classification and regression tasks. Moreover, it allows to construct an FRBS model defined by human experts. FRBSs are based on the concept of fuzzy sets, proposed by Zadeh in 1965, which aims at representing the reasoning of human experts in a set of IF-THEN rules, to handle real-life problems in, e.g., control, prediction and inference, data mining, bioinformatics data processing, and robotics. FRBSs are also known as fuzzy inference systems and fuzzy models. During the modeling of an FRBS, there are two important steps that need to be conducted: structure identification and parameter estimation. Nowadays, there exists a wide variety of algorithms to generate fuzzy IF-THEN rules automatically from numerical data, covering both steps. Approaches that have been used in the past are, e.g., heuristic procedures, neuro-fuzzy techniques, clustering methods, genetic algorithms, squares methods, etc. Furthermore, in this version we provide a universal framework named 'frbsPMML', which is adopted from the Predictive Model Markup Language (PMML), for representing FRBS models. PMML is an XML-based language to provide a standard for describing models produced by data mining and machine learning algorithms. Therefore, we are allowed to export and import an FRBS model to/from 'frbsPMML'. Finally, this package aims to implement the most widely used standard procedures, thus offering a standard package for FRBS modeling to the R community.

Authors:Lala Septem Riza, Christoph Bergmeir, Francisco Herrera, and Jose Manuel Benitez

frbs_3.2-0.tar.gz
frbs_3.2-0.tar.gz(r-4.5-noble)frbs_3.2-0.tar.gz(r-4.4-noble)
frbs_3.2-0.tgz(r-4.4-emscripten)frbs_3.2-0.tgz(r-4.3-emscripten)
frbs.pdf |frbs.html
frbs/json (API)

# Install 'frbs' in R:
install.packages('frbs', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

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This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

5.02 score 10 stars 1 packages 75 scripts 1.2k downloads 2 mentions 14 exports 0 dependencies

Last updated 5 years agofrom:3aba8824ee. Checks:ERROR: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesFAILDec 19 2024
R-4.5-linuxNOTEDec 19 2024

Exports:data.gen3ddefuzzifierdenorm.dataECMfrbs.genfrbs.learnfrbsPMMLfuzzifierinferencenorm.dataplotMFread.frbsPMMLrulebasewrite.frbsPMML

Dependencies:

frbs: Fuzzy Rule-based Systems for Classification and Regression in R

Rendered fromlala2015frbs.ltxusingR.rsp::texon Dec 19 2024.

Last update: 2019-12-15
Started: 2019-12-15

frbsPMML: A Universal Representation Framework for Fuzzy Rule-Based Systems Based on PMML

Rendered fromlala2015pmml.Rtexusingutils::Sweaveon Dec 19 2024.

Last update: 2019-12-15
Started: 2019-12-15

Readme and manuals

Help Manual

Help pageTopics
Getting started with the frbs packagefrbs-package frbs
ANFIS model buildingANFIS
ANFIS updating functionANFIS.update
A data generatordata.gen3d
Defuzzifier to transform from linguistic terms to crisp valuesdefuzzifier
DENFIS model buildingDENFIS
DENFIS prediction functionDENFIS.eng
The data de-normalizationdenorm.data
FIR.DM updating functionDM.update
Evolving Clustering MethodECM
FH.GBML model buildingFH.GBML
FIR.DM model buildingFIR.DM
FRBCS.CHI model buildingFRBCS.CHI
FRBCS: prediction phaseFRBCS.eng
FRBCS.W model buildingFRBCS.W
The prediction phasefrbs.eng
The frbs model generatorfrbs.gen
The frbs model building functionfrbs.learn
Data set of the packagefrbsData
The object factory for frbs objectsfrbs-object frbsObjectFactory
The frbsPMML generatorfrbsPMML
FS.HGD model buildingFS.HGD
Transforming from crisp set into linguistic termsfuzzifier
GFS.FR.MOGUL model buildingGFS.FR.MOGUL
GFS.FR.MOGUL: The prediction phaseGFS.FR.MOGUL.test
GFS.GCCL model buildingGFS.GCCL
GFS.GCCL.test: The prediction phaseGFS.GCCL.eng
GFS.LT.RS model buildingGFS.LT.RS
GFS.LT.RS: The prediction phaseGFS.LT.RS.test
GFS.Thrift model buildingGFS.Thrift
GFS.Thrift: The prediction phaseGFS.Thrift.test
FS.HGD updating functionHGD.update
HyFIS model buildingHyFIS
HyFIS updating functionHyFIS.update
The process of fuzzy reasoninginference
The data normalizationnorm.data
The plotting functionplotMF
The frbs prediction stagepredict predict.frbs
The frbsPMML readerread.frbsPMML
The rule checking functionrulebase
The subtractive clustering and fuzzy c-means (SBC) model buildingSBC
SBC prediction phaseSBC.test
SLAVE model buildingSLAVE
SLAVE.test: The prediction phaseSLAVE.test
The summary function for frbs objectssummary.frbs
WM model buildingWM
The frbsPMML writerwrite.frbsPMML