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lfl (version 1.3)

Linguistic Fuzzy Logic

Description

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).

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Version

Install

install.packages('lfl')

Monthly Downloads

435

Version

1.3

License

GPL (>= 3.0)

Maintainer

Michal Burda

Last Published

April 22nd, 2016

Functions in lfl (1.3)

Reduce the size of rule base

Composition of Fuzzy Relations

Plot a 'fsets' object

Implicational aggregation of rules' consequents into a fuzzy set

Compute membership degrees of values to the fuzzy set

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

Return the first part of an instance of the fsets class

Print an instance of the frbe class

Compute truth-degrees of rules on data

Transform data into a set of fuzzy attributes using triangular or raised cosine shapes of the fuzzy sets

Test whether x is a valid object of the farules class

Searching for fuzzy association rules

Evaluate the performance of the FRBE forecast

A class of a table with several fuzzy sets.

Compute forecast errors

Test whether x is a valid object of the frbe class

Determine whether the first set of predicates is more specific (or equal) than the other.

Extract antecedent-part (LHS) of the rules in a list

Algebra for Fuzzy Sets

Return the last part of an instance of the farules class

Combine several 'fsets' objects into a single one

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

Extract consequent-part (RHS) of the rules in a list

Linguistic Fuzzy Logic

Return the first part of an instance of the farules class

A class of rules with statistical characteristics.

Print an instance of the fsets class

Test whether x is a valid object of the fsets class

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

Select several rows and columns from a data object

Compute rule base coverage of data

as.matrix.fsets

Convert a 'fsets' object into matrix

Return vector of values from given interval

Return the last part of an instance of the fsets class

Convert fuzzy set into a crisp numeric value

Print an instance of the farules class

Callback-based Multiplication of Matrices

Transform data into a set of linguistic fuzzy attributes

as.data.frame.farules

Convert the 'farules' object into a data frame