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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.

Documentation

The complete documentation of the package is available in this vignette.

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")

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Version

Install

install.packages('lfl')

Monthly Downloads

618

Version

2.3.0

License

GPL-3

Maintainer

Michal Burda

Last Published

June 27th, 2025

Functions in lfl (2.3.0)

as.data.frame.fsets

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.farules

Convert the instance of the farules() S3 class into a data frame. Empty farules() object is converted into an empty data.frame().

Combine several 'fsets' objects into a single one

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.

Extract antecedent-part (left-hand side) of rules in a list

Composition of Fuzzy Relations

Extract consequent-part (right-hand side) of rules in a list

Algebra for Fuzzy Sets

Modify algebra's way of computing with NA values.

aggregateConsequents

Aggregation of fired consequents into a resulting fuzzy set

Fuzzy Rule-Based Ensemble (FRBE) of time-series forecasts

Context for linguistic expressions

Return equifrequent breaks

Create an instance of S3 class farules which represents a set of fuzzy association rules and their statistical characteristics.

Evaluate the performance of the FRBE forecast

Evaluate rules and obtain truth-degrees

Transform data into a fsets S3 class using shapes derived from triangles or raised cosines

defaultHedgeParams

A list of the parameters that define the shape of the hedges.

Test whether x is a valid object of the S3 ft class

Convert fuzzy set into a crisp numeric value

Inverse of the fuzzy transform

Create a function that computes linguistic horizons

Test whether x inherits from the S3 farules class.

Return equidistant breaks

Determine whether the first set x of predicates is more specific (or equal) than y with respect to vars and specs.

Creating linguistic context directly from values

lfl - Linguistic Fuzzy Logic

S3 class representing a set of fuzzy sets on the fixed universe

Fuzzy transform

Compute Mean Absolute Scaled Error (MASE)

Creator of functions representing linguistic expressions

Callback-based Multiplication of Matrices

Print an instance of the fsets() class

Transform data into a fsets S3 class of linguistic fuzzy attributes

Return vector of values from given interval

Print an instance of the frbe() class

Print the linguistic context

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.)

Linguistic hedges

Searching for fuzzy association rules

Print an instance of the algebra() S3 class in a human readable form.

Compute rule base coverage of data

Test whether x is a valid object of the S3 frbe class

Plot membership degrees stored in the instance of the S3 class fsets() as a line diagram.

Perform a Perception-based Logical Deduction (PbLD) with given rule-base on given dataset

Compute Symmetric Mean Absolute Percentage Error (SMAPE)

From a set of rules, remove each rule for which another rule exists that is more specific.

Print an instance of the farules() S3 class in a human readable form.

Test whether x is a valid object of the S3 fsets class

Reduce the size of rule base

Compute Root Mean Squared Error (RMSE)

Factories for functions that convert numeric data into membership degrees of fuzzy sets

Compactly display the internal structure of an instance of the fsets() class

Deprecated functions to compute membership degrees of numeric fuzzy sets

A factory function for creation of sugeno-integrals.