Package: lfl 2.4.0

lfl: Linguistic Fuzzy Logic

Various algorithms related to linguistic fuzzy logic: mining for linguistic fuzzy association rules, composition of fuzzy relations, performing Mamdani, implicative, and 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 the fuzzy transform.

Authors:Michal Burda [aut, cre]

lfl_2.4.0.tar.gz
lfl_2.4.0.zip(r-4.7)lfl_2.4.0.zip(r-4.6)lfl_2.4.0.zip(r-4.5)
lfl_2.4.0.tgz(r-4.6-x86_64)lfl_2.4.0.tgz(r-4.6-arm64)lfl_2.4.0.tgz(r-4.5-x86_64)lfl_2.4.0.tgz(r-4.5-arm64)
lfl_2.4.0.tar.gz(r-4.7-arm64)lfl_2.4.0.tar.gz(r-4.7-x86_64)lfl_2.4.0.tar.gz(r-4.6-arm64)lfl_2.4.0.tar.gz(r-4.6-x86_64)
lfl_2.4.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
lfl/json (API)

# Install 'lfl' in R:

install.packages('lfl', repos = c('https://beerda.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/beerda/lfl/issues

Uses libs:

c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

On CRAN:

association-rules forecast-model fuzzy-logic inference-rules cpp openmp

5.68 score 8 stars 30 scripts 441 downloads 89 exports 50 dependencies

Last updated from:26578d6300. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	210
linux-devel-x86_64	OK	195
source / vignettes	OK	214
linux-release-arm64	OK	197
linux-release-x86_64	OK	193
macos-release-arm64	OK	112
macos-release-x86_64	OK	360
macos-oldrel-arm64	OK	141
macos-oldrel-x86_64	OK	277
windows-devel	OK	166
windows-release	OK	188
windows-oldrel	OK	218
wasm-release	OK	187

Exports:aggregateConsequents algebra allowed.lingexpr antecedents as.ctx3 as.ctx3bilat as.ctx5 as.ctx5bilat compose consequents ctx3 ctx3bilat ctx5 ctx5bilat defaultHedgeParams defuzz dragonfly equidist equifreq evalfrbe farules fcut fire frbe fsets ft ftinv goedel.biresiduum goedel.residuum goedel.tconorm goedel.tnorm goguen.biresiduum goguen.residuum goguen.tconorm goguen.tnorm hedge horizon infer invol.neg is.algebra is.ctx3 is.ctx3bilat is.ctx5 is.ctx5bilat is.farules is.frbe is.fsets is.ft is.specific kleene lcut lingexpr lowerBound lowerEst lukas.biresiduum lukas.residuum lukas.tconorm lukas.tnorm mase minmax mult nelson pbld perceive pgoedel.tconorm pgoedel.tnorm pgoguen.tconorm pgoguen.tnorm plukas.tconorm plukas.tnorm quantifier raisedcos raisedcosine rbcoverage reduce rmse searchrules slices smape sobocinski specs specs<-strict.neg sugeno triangle triangular upperBound vars vars<-

Dependencies:class cli codetools colorspace cpp11 curl e1071 farver foreach forecast fracdiff generics ggplot2 glue gtable isoband iterators jsonlite labeling lattice lifecycle lmtest magrittr MASS nlme nnet pillar pkgconfig plyr proxy quadprog quantmod R6 RColorBrewer Rcpp RcppArmadillo rlang S7 scales tibble timeDate tseries TTR urca utf8 vctrs viridisLite withr xts zoo

lfl: An R Package for Linguistic Fuzzy Logic

Rendered frommain.pdf.asisusingR.rsp::asis

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

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Aggregation of fired consequents into a resulting fuzzy set	aggregateConsequents
Algebra for Fuzzy Sets	algebra 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 list	antecedents
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 one	cbind.fsets
Composition of Fuzzy Relations	compose
Extract consequent-part (right-hand side) of rules in a list	consequents
Context for linguistic expressions	as.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 value	defuzz
Return equidistant breaks	equidist
Return equifrequent breaks	equifreq
Evaluate the performance of the FRBE forecast	evalfrbe
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 cosines	fcut fcut.data.frame fcut.default fcut.factor fcut.logical fcut.matrix fcut.numeric
Evaluate rules and obtain truth-degrees	fire
Fuzzy Rule-Based Ensemble (FRBE) of time-series forecasts	frbe
S3 class representing a set of fuzzy sets on the fixed universe	fsets specs specs<- vars vars<-
Fuzzy transform	ft
Inverse of the fuzzy transform	ftinv
Linguistic hedges	hedge
Create a function that computes linguistic horizons	horizon
Perform Mamdani or implicative fuzzy inference with given rule-base on given dataset	infer
Test whether 'x' inherits from the S3 'farules' class.	is.farules
Test whether 'x' is a valid object of the S3 'frbe' class	is.frbe
Test whether 'x' is a valid object of the S3 'fsets' class	is.fsets
Test whether 'x' is a valid object of the S3 'ft' class	is.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 attributes	lcut lcut.data.frame lcut.default lcut.factor lcut.logical lcut.matrix lcut.numeric
Creator of functions representing linguistic expressions	allowed.lingexpr lingexpr
Compute Mean Absolute Scaled Error (MASE)	mase
Creating linguistic context directly from values	minmax
Callback-based Multiplication of Matrices	mult
Perform a Perception-based Logical Deduction (PbLD) with given rule-base on given dataset	pbld
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 context	print.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()' class	print.frbe
Print an instance of the 'fsets()' class	print.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 data	rbcoverage
Reduce the size of rule base	reduce
Compute Root Mean Squared Error (RMSE)	rmse
Searching for fuzzy association rules	searchrules
Return vector of values from given interval	slices
Compute Symmetric Mean Absolute Percentage Error (SMAPE)	smape
Modify algebra's way of computing with 'NA' values.	algebraNA dragonfly kleene lowerBound lowerEst nelson sobocinski upperBound
Compactly display the internal structure of an instance of the 'fsets()' class	str.fsets
A factory function for creation of sugeno-integrals.	sugeno
Deprecated functions to compute membership degrees of numeric fuzzy sets	raisedcos triangle
Factories for functions that convert numeric data into membership degrees of fuzzy sets	raisedcosine triangular