SparseConcept: R6 class for a fuzzy concept with sparse internal...

Description Methods Examples

Description

This class implements the data structure and methods for fuzzy concepts.

Methods

Public methods


Method new()

Creator for objects of class SparseConcept

Usage
SparseConcept$new(extent, intent)
Arguments
extent

(SparseSet) The extent of the concept.

intent

(SparseSet) The intent of the concept.

Returns

An object of class SparseConcept.


Method get_extent()

Internal SparseSet for the extent

Usage
SparseConcept$get_extent()
Returns

The SparseSet representation of the extent.


Method get_intent()

Internal SparseSet for the intent

Usage
SparseConcept$get_intent()
Returns

The SparseSet representation of the intent.


Method print()

Prints the concept to console

Usage
SparseConcept$print()
Returns

A string with the elements of the set and their grades between brackets .


Method to_latex()

Write the concept in LaTeX format

Usage
SparseConcept$to_latex(print = TRUE)
Arguments
print

(logical) Print to output?

Returns

The fuzzy concept in LaTeX.


Method clone()

The objects of this class are cloneable with this method.

Usage
SparseConcept$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

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# Build a formal context and find its concepts
fc_planets <- FormalContext$new(planets)
fc_planets$find_concepts()

# Print the first three concepts
fc_planets$concepts[1:3]

# Select the first concept:
C <- fc_planets$concepts[1][[1]]

# Get its extent and intent
C$get_extent()
C$get_intent()

neuroimaginador/fcaR documentation built on Dec. 9, 2020, 5:42 a.m.