RandomDistributiveContext

Generates a random formal context that is guaranteed to produce a
Distributive Concept Lattice.
It relies on Birkhoff's Representation Theorem: The lattice of order ideals
of a Poset is always distributive. The context is constructed such that
objects and attributes are the elements of the poset, and the incidence
relation is \(g I m \iff \neg(g \ge m)\).

Provides tools to perform fuzzy formal concept analysis, presented in Wille (1982) <doi:10.1007/978-3-642-01815-2_23> and in Ganter and Obiedkov (2016) <doi:10.1007/978-3-662-49291-8>. It provides functions to load and save a formal context, extract its concept lattice and implications. In addition, one can use the implications to compute semantic closures of fuzzy sets and, thus, build recommendation systems. Matrix factorization is provided by the GreConD+ algorithm (Belohlavek and Trneckova, 2024 <doi:10.1109/TFUZZ.2023.3330760>).

Domingo Lopez Rodriguez

fcaR

Formal Concept Analysis

Angel Mora

Jesus Dominguez

Ana Villalon

RandomDistributiveContext function

<dl><dt>n_elements</dt>
<dd>Number of elements in the underlying Poset.</dd>
<dt>density</dt>
<dd>Probability of an order relation \(a \le b\).</dd></dl>

Arguments

Generate a Random Distributive Context — RandomDistributiveContext

<dl>

<dt>n_elements</dt>
<dd>Number of elements in the underlying Poset.</dd>


<dt>density</dt>
<dd>Probability of an order relation \(a \le b\).</dd>

</dl>

RandomDistributiveContext: Generate a Random Distributive Context

Description

Usage

Value

Arguments