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

In neuroimaginador/fcaR: Formal Concept Analysis

Description

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

Methods

Public methods

• SparseConcept$new()

• SparseConcept$get_extent()

• SparseConcept$get_intent()

• SparseConcept$print()

• SparseConcept$to_latex()

• SparseConcept$clone()

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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.

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Method get_extent()

Internal SparseSet for the extent

Usage

SparseConcept$get_extent()

Returns

The SparseSet representation of the extent.

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Method get_intent()

Internal SparseSet for the intent

Usage

SparseConcept$get_intent()

Returns

The SparseSet representation of the intent.

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Method print()

Prints the concept to console

Usage

SparseConcept$print()

Returns

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

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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.

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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

# 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.