Package: lfl 2.2.1

Michal Burda

lfl: Linguistic Fuzzy Logic

Various algorithms related to linguistic fuzzy logic: mining for linguistic fuzzy association rules, composition of fuzzy relations, performing perception-based logical deduction (PbLD), and forecasting time-series using fuzzy rule-based ensemble (FRBE). The package also contains basic fuzzy-related algebraic functions capable of handling missing values in different styles (Bochvar, Sobocinski, Kleene etc.), computation of Sugeno integrals and fuzzy transform.

Authors:Michal Burda [aut, cre]

lfl_2.2.1.tar.gz
lfl_2.2.1.tar.gz(r-4.5-noble)lfl_2.2.1.tar.gz(r-4.4-noble)
lfl_2.2.1.tgz(r-4.4-emscripten)lfl_2.2.1.tgz(r-4.3-emscripten)
lfl.pdf |lfl.html✨
lfl/json (API)
NEWS

# Install 'lfl' in R:
install.packages('lfl', repos = 'https://cloud.r-project.org')
Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

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

cppopenmp

2.70 score 1 stars 675 downloads 86 exports 52 dependencies

Last updated 5 months agofrom:f08c9ffd79. Checks:3 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 22 2025
R-4.5-linux-x86_64OKMar 22 2025
R-4.4-linux-x86_64OKMar 22 2025

Exports:aggregateConsequentsalgebraallowed.lingexprantecedentsas.ctx3as.ctx3bilatas.ctx5as.ctx5bilatcomposeconsequentsctx3ctx3bilatctx5ctx5bilatdefaultHedgeParamsdefuzzdragonflyequidistequifreqevalfrbefarulesfcutfirefrbefsetsftftinvgoedel.biresiduumgoedel.residuumgoedel.tconormgoedel.tnormgoguen.biresiduumgoguen.residuumgoguen.tconormgoguen.tnormhedgehorizoninvol.negis.algebrais.ctx3is.ctx3bilatis.ctx5is.ctx5bilatis.farulesis.frbeis.fsetsis.ftis.specifickleenelcutlingexprlowerEstlukas.biresiduumlukas.residuumlukas.tconormlukas.tnormmaseminmaxmultnelsonpbldperceivepgoedel.tconormpgoedel.tnormpgoguen.tconormpgoguen.tnormplukas.tconormplukas.tnormquantifierraisedcosraisedcosinerbcoveragereducermsesearchrulesslicessmapesobocinskispecsspecs<-strict.negsugenotriangletriangularvarsvars<-

Dependencies:classclicodetoolscolorspacecurle1071fansifarverforeachforecastfracdiffgenericsggplot2gluegtableisobanditeratorsjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigplyrproxyquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo

lfl: An R Package for Linguistic Fuzzy Logic

Rendered frommain.pdf.asisusingR.rsp::asison Mar 22 2025.

Last update: 2021-08-23
Started: 2021-08-23

Citation

Burda M, Štěpnička M (2021). “lfl: An R package for linguistic fuzzy logic.” Fuzzy Sets and Systems. ISSN 0165-0114, doi:10.1016/j.fss.2021.07.007.

Corresponding BibTeX entry: 

  @Article{,
    title = {lfl: An {R} package for linguistic fuzzy logic},
    author = {Michal Burda and Martin Štěpnička},
    journal = {Fuzzy Sets and Systems},
    year = {2021},
    issn = {0165-0114},
    doi = {10.1016/j.fss.2021.07.007},
  }

Readme and manuals

lfl

The lfl package provides various algorithms related to linguistic fuzzy logic: mining for linguistic fuzzy association rules, composition of fuzzy relations, performing perception-based logical deduction (PbLD), and forecasting time-series using fuzzy rule-based ensemble (FRBE). The package also contains basic fuzzy-related algebraic functions capable of handling missing values in different styles (Bochvar, Sobocinski, Kleene etc.), computation of Sugeno integrals and fuzzy transform.

Installation

To install the stable version from CRAN, simply issue the following command within your R session:

install.packages("lfl")

If you want to install the development version instead, type:

install.packages("devtools")
devtools::install_github("beerda/lfl")

Help Manual

Help pageTopics
Aggregation of fired consequents into a resulting fuzzy setaggregateConsequents
Algebra for Fuzzy Setsalgebra goedel.biresiduum goedel.residuum goedel.tconorm goedel.tnorm goguen.biresiduum goguen.residuum goguen.tconorm goguen.tnorm invol.neg is.algebra lukas.biresiduum lukas.residuum lukas.tconorm lukas.tnorm pgoedel.tconorm pgoedel.tnorm pgoguen.tconorm pgoguen.tnorm plukas.tconorm plukas.tnorm strict.neg
Extract antecedent-part (left-hand side) of rules in a listantecedents
Convert the instance of the 'farules()' S3 class into a data frame. Empty 'farules()' object is converted into an empty 'data.frame()'.as.data.frame.farules
Convert an object of 'fsets' class into a matrix or data frame This function converts an instance of S3 class fsets into a matrix or a data frame. The 'vars()' and 'specs()' attributes of the original object are deleted.as.data.frame.fsets as.matrix.fsets
Take a sequence of instances of S3 class 'farules()' and combine them into a single object. An error is thrown if some argument does not inherit from the 'farules()' class.c.farules
Combine several 'fsets' objects into a single onecbind.fsets
Composition of Fuzzy Relationscompose
Extract consequent-part (right-hand side) of rules in a listconsequents
Context for linguistic expressionsas.ctx3 as.ctx3.ctx3 as.ctx3.ctx3bilat as.ctx3.ctx5 as.ctx3.ctx5bilat as.ctx3.default as.ctx3bilat as.ctx3bilat.ctx3 as.ctx3bilat.ctx3bilat as.ctx3bilat.ctx5 as.ctx3bilat.ctx5bilat as.ctx3bilat.default as.ctx5 as.ctx5.ctx3 as.ctx5.ctx3bilat as.ctx5.ctx5 as.ctx5.ctx5bilat as.ctx5.default as.ctx5bilat as.ctx5bilat.ctx3 as.ctx5bilat.ctx3bilat as.ctx5bilat.ctx5 as.ctx5bilat.ctx5bilat as.ctx5bilat.default ctx ctx3 ctx3bilat ctx5 ctx5bilat is.ctx3 is.ctx3bilat is.ctx5 is.ctx5bilat
A list of the parameters that define the shape of the hedges.defaultHedgeParams
Convert fuzzy set into a crisp numeric valuedefuzz
Return equidistant breaksequidist
Return equifrequent breaksequifreq
Evaluate the performance of the FRBE forecastevalfrbe
Create an instance of S3 class 'farules' which represents a set of fuzzy association rules and their statistical characteristics.farules
Transform data into a 'fsets' S3 class using shapes derived from triangles or raised cosinesfcut fcut.data.frame fcut.default fcut.factor fcut.logical fcut.matrix fcut.numeric
Evaluate rules and obtain truth-degreesfire
Fuzzy Rule-Based Ensemble (FRBE) of time-series forecastsfrbe
S3 class representing a set of fuzzy sets on the fixed universefsets specs specs<- vars vars<-
Fuzzy transformft
Inverse of the fuzzy transformftinv
Linguistic hedgeshedge
Create a function that computes linguistic horizonshorizon
Test whether 'x' inherits from the S3 'farules' class.is.farules
Test whether 'x' is a valid object of the S3 'frbe' classis.frbe
Test whether 'x' is a valid object of the S3 'fsets' classis.fsets
Test whether 'x' is a valid object of the S3 'ft' classis.ft
Determine whether the first set 'x' of predicates is more specific (or equal) than 'y' with respect to 'vars' and 'specs'.is.specific
Transform data into a 'fsets' S3 class of linguistic fuzzy attributeslcut lcut.data.frame lcut.default lcut.factor lcut.logical lcut.matrix lcut.numeric
Creator of functions representing linguistic expressionsallowed.lingexpr lingexpr
Compute Mean Absolute Scaled Error (MASE)mase
Creating linguistic context directly from valuesminmax
Callback-based Multiplication of Matricesmult
Perform a Perception-based Logical Deduction (PbLD) with given rule-base on given datasetpbld
From a set of rules, remove each rule for which another rule exists that is more specific.perceive
Plot membership degrees stored in the instance of the S3 class 'fsets()' as a line diagram.plot.fsets
Print an instance of the 'algebra()' S3 class in a human readable form.print.algebra
Print the linguistic contextprint.ctx3 print.ctx3bilat print.ctx5 print.ctx5bilat
Print an instance of the 'farules()' S3 class in a human readable form.print.farules
Print an instance of the 'frbe()' classprint.frbe
Print an instance of the 'fsets()' classprint.fsets
A quantifier is a function that computes a fuzzy truth value of a claim about the quantity. This function creates the <1>-type quantifier. (See the examples below on how to use it as a quantifier of the <1,1> type.)quantifier
Compute rule base coverage of datarbcoverage
Reduce the size of rule basereduce
Compute Root Mean Squared Error (RMSE)rmse
Searching for fuzzy association rulessearchrules
Return vector of values from given intervalslices
Compute Symmetric Mean Absolute Percentage Error (SMAPE)smape
Modify algebra's way of computing with 'NA' values.algebraNA dragonfly kleene lowerEst nelson sobocinski
A factory function for creation of sugeno-integrals.sugeno
Deprecated functions to compute membership degrees of numeric fuzzy setsraisedcos triangle
Factories for functions that convert numeric data into membership degrees of fuzzy setsraisedcosine triangular