Package: fcaR 1.7.0

Domingo Lopez Rodriguez

fcaR: Formal Concept Analysis

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>).

Authors:Domingo Lopez Rodriguez [aut, cre], Angel Mora [aut], Jesus Dominguez [aut], Ana Villalon [aut]

fcaR_1.7.0.tar.gz
fcaR_1.7.0.zip(r-4.7)fcaR_1.7.0.zip(r-4.6)fcaR_1.7.0.zip(r-4.5)
fcaR_1.7.0.tgz(r-4.6-x86_64)fcaR_1.7.0.tgz(r-4.6-arm64)fcaR_1.7.0.tgz(r-4.5-x86_64)fcaR_1.7.0.tgz(r-4.5-arm64)
fcaR_1.7.0.tar.gz(r-4.7-arm64)fcaR_1.7.0.tar.gz(r-4.7-x86_64)fcaR_1.7.0.tar.gz(r-4.6-arm64)fcaR_1.7.0.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
fcaR/json (API)

# Install 'fcaR' in R:
install.packages('fcaR', repos = c('https://malaga-fca-group.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/malaga-fca-group/fcar/issues

Pkgdown/docs site:https://neuroimaginador.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • cobre32 - Data for Differential Diagnosis for Schizophrenia
  • cobre61 - Data for Differential Diagnosis for Schizophrenia
  • guesswho - Data for Guess Who Board Game
  • planets - Planets data
  • vegas - Data for Tourist Destination in Las Vegas

On CRAN:

Conda:

formal-concept-analysiscpp

8.19 score 10 stars 120 scripts 476 downloads 42 exports 26 dependencies

Last updated from:f1fac71192. Checks:12 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK278
linux-devel-x86_64OK291
source / vignettesOK438
linux-release-arm64OK272
linux-release-x86_64OK291
macos-release-arm64OK205
macos-release-x86_64OK408
macos-oldrel-arm64OK207
macos-oldrel-x86_64OK486
windows-develOK328
windows-releaseOK298
windows-oldrelOK301
wasm-releaseFAIL212

Exports:%-%%&%%<=%%==%%|%%~%%entails%%holds_in%%respects%as_Setas_vectorBondLatticebondscalculate_gradescalculate_separationConceptConceptLatticeconceptRegistryConceptSetcontext_from_jsonequivalencesRegistryfcaR_optionsfetch_contextfind_causal_rulesFormalContextget_fcarepository_contextsimplications_from_jsonImplicationSetis_bondlattice_from_jsonlattice_plotparse_implicationsprint_repo_detailsRandomContextRandomDistributiveContextrandomize_contextrules_from_jsonRuleSetsave_tikzscalingRegistryselect_repository_contextSet

Dependencies:BHclicpp11dplyrgenericsgluelatticelifecyclemagrittrMatrixpillarpkgconfigpurrrR6Rcppregistryrlangsettingsstringistringrtibbletidyrtidyselectutf8vctrswithr

Lattice properties
Introduction | 1. Checking lattice properties | Understanding the properties | Example: A non-distributive lattice ($M_3$) | 2. Arrow Relations
Rendered fromlattice_properties.Rmdusingknitr::rmarkdown

Last update: 2026-03-26
Started: 2025-11-28

Working with Bonds
Introduction | Computing Bonds | Computation Methods | The BondLattice Object | Visualization | Extracting Bonds | The Core Bond | Verifying Bonds | Similarity and Complexity Metrics | Order-Theoretic Properties | Summary
Rendered frombonds.Rmdusingknitr::rmarkdown

Last update: 2026-03-11
Started: 2026-03-09

Using FormalContexts and ConceptLattices
Introduction | Datasets | Working with Formal Contexts | Plotting, printing and latex-ing the FormalContext | Importing a Formal Context from File | Dual Formal Context | Closures | Clarification and Reduction | Extracting Implications and Concepts | Protoconcepts | Standard Context | Saving and loading | Concept Lattice | Plot, print and LaTeX | Getting all extents, intents and retrieving concepts | Concept support | Sublattices | Subconcepts, superconcepts, infimum and supremum | Join- and meet- irreducible elements
Rendered fromconcept_lattice.Rmdusingknitr::rmarkdown

Last update: 2026-02-17
Started: 2019-12-14

Working with ImplicationSets
Introduction | Datasets | Extraction of the canonical basis of implications | Validity of implications | Cardinality, size and support of the implication set | Export to LaTeX | Filtering of implications | Simplification Logic | Entailment and equivalence of implications | Standard Context | Recommendation systems
Rendered fromimplications.Rmdusingknitr::rmarkdown

Last update: 2026-02-17
Started: 2020-01-07

JSON Export and Import
Setup | FormalContext | Creating and Exporting | Importing | Recursive Export | ConceptLattice | ImplicationSet | RuleSet | Summary
Rendered fromjson_export_import.Rmdusingknitr::rmarkdown

Last update: 2026-02-12
Started: 2026-02-12

Conceptual Scaling
Introduction and Motivation | Types of Scaling | Nominal scaling | Ordinal scaling | Interordinal scaling | Biordinal scaling | Interval scaling | Scaling in fcaR | Available scales | Applying scales | Scale contexts | Background knowledge | Concepts and implications | Another example
Rendered fromconceptual-scaling.Rmdusingknitr::rmarkdown

Last update: 2026-02-11
Started: 2021-03-16

Mining Causal Association Rules
Introduction | The Approach | Example 1: Direct Causality | Example 2: Simpson's Paradox (Spurious Correlation) | Conclusion
Rendered fromcausal.Rmdusingknitr::rmarkdown

Last update: 2026-02-10
Started: 2026-02-10

Data Manipulation with fcaR and dplyr
Introduction | Setup | Part 1: Context Manipulation | 1.1 Renaming and Feature Engineering | 1.2 Filtering and Selecting | Part 2: Mining and Filtering Implications | 2.1 Filtering by Metrics | 2.2 Semantic Filtering | 2.3 Complex Pipelines | Conclusion
Rendered fromfcaR_dplyr.Rmdusingknitr::rmarkdown

Last update: 2026-01-19
Started: 2026-01-19

Matrix Factorization
Introduction | 1. Fuzzy Matrix Factorization (GreConD+) | Interpretation | Verification | 2. Boolean Matrix Factorization (ASSO) | References
Rendered frommatrix_factorization.Rmdusingknitr::rmarkdown

Last update: 2025-12-11
Started: 2025-11-17

Advanced Random Contexts
Introduction | 1. Dirichlet Distribution for Realistic Data | 2. Randomization via Edge Swapping | 3. Generating Distributive Lattices
Rendered fromrandom_contexts.Rmdusingknitr::rmarkdown

Last update: 2025-11-28
Started: 2025-11-21

Advanced lattice metrics
Introduction | Stability | Separation | Fuzzy density | Putting it all together
Rendered fromadvanced_lattice_metrics.Rmdusingknitr::rmarkdown

Last update: 2025-11-19
Started: 2025-11-19

Creating Formal Contexts in fcaR
1. Creating from R Data Structures | From a matrix | From a data frame | 2. Importing from Local Files | CXT Format (.cxt) | CSV Files (.csv) | 3. Fetching from the FCA Repository | Browsing the Repository | Downloading a Specific Context | 4. Interactive Use: The RStudio Addin | How to Launch It | What Does the Addin Do? | Summary of Methods
Rendered fromcreating_contexts.Rmdusingknitr::rmarkdown

Last update: 2025-11-19
Started: 2025-11-19

Fuzzy formal concept analysis
Introduction | 1. Creating a fuzzy formal context | 2. Fuzzy logics and operators | Available logics | Changing the logic | 3. Mining fuzzy concepts | 4. Visualization | 5. Fuzzy implications | Support and confidence | 6. Fuzzy closure and recommendation | Summary of formulas
Rendered fromfuzzy_fca.Rmdusingknitr::rmarkdown

Last update: 2025-11-19
Started: 2025-11-19

Visualizing concept lattices: from R to LaTeX
1. Standard visualization | Layout algorithms | 1. Sugiyama layout (layered) | 2. Force-directed layout (organic) | 2. Labeling modes | Reduced labeling | Full labeling | Empty (structure only) | 3. Exporting to LaTeX (TikZ) | Saving to a file | How to use it in LaTeX
Rendered fromlattice_visualization.Rmdusingknitr::rmarkdown

Last update: 2025-11-19
Started: 2025-11-19

Extending fcaR: Equivalence Rules for Implications
Introduction | The Registry | Use of the Rules | Definition of New Equivalence Rules | An Example
Rendered fromextending_equivalence.Rmdusingknitr::rmarkdown

Last update: 2025-09-26
Started: 2020-07-18

Integration with the arules package
Introduction | Datasets | Converting between formal contexts and transactions objects | Importing a transactions object | Exporting a FormalContext | Converting between implication sets and rules objects | Importing rules as an implication set | Exporting ImplicationSets to rules format | Final considerations
Rendered fromarules.Rmdusingknitr::rmarkdown

Last update: 2025-09-26
Started: 2020-01-07

Readme and manuals

Help Manual

Help pageTopics
Difference in Sets%-%
Intersection (Logical AND) of Fuzzy Sets%&%
Partial Order in Sets and Concepts%<=%
Equality in Sets and Concepts%==%
Equivalence of sets of implications%~%
Entailment between implication sets%entails%
Implications that hold in a Formal Context%holds_in%
Union (Logical OR) of Fuzzy Sets%or% %|%
Check if Set or FormalContext respects an ImplicationSet%respects%
Convert Named Vector to Setas_Set
Convert Set to vectoras_vector
R6 class for a Bond LatticeBondLattice
Compute bonds between two formal contextsbonds
Compute bonds via MCIS (backtracking on pre-computed concepts)bonds_mcis
Compute bonds via standard implication-based methodbonds_standard
Calculate Fuzzy Densitycalculate_density
Calculate Concept Grades (Levels)calculate_grades
Calculate Concept Separationcalculate_separation
Calculate Concept Stabilitycalculate_stability
Data for Differential Diagnosis for Schizophreniacobre32
Data for Differential Diagnosis for Schizophreniacobre61
Compute Labels and Colors for Lattice Nodescompute_labels_and_colors
R6 class for a fuzzy concept with sparse internal representationConcept
R6 class for a concept latticeConceptLattice
Concept Miners RegistryconceptRegistry
R6 class for a set of conceptsConceptSet
Import FormalContext from JSONcontext_from_json
dplyr verbs for RuleSetarrange.RuleSet dplyr_rules
dplyr verbs for FormalContextdplyr_verbs select.FormalContext
Equivalence Rules RegistryequivalencesRegistry
Export Layout to TikZ (LaTeX)export_to_tikz
Set or get options for fcaRfcaR_options
Fetch a Formal Context from the FCA Repositoryfetch_context
Causal Association Rulesfind_causal_rules
R6 class for a formal contextFormalContext
Get Metadata from the FCA Repositoryget_fcarepository_contexts
Data for Guess Who Board Gameguesswho
Import ImplicationSet from JSONimplications_from_json
R6 class for an Implication SetImplicationSet
Verify if a relation is a bond between two formal contextsis_bond
Import ConceptLattice from JSONlattice_from_json
Plot Concept Latticelattice_plot
Parses a string into an implicationparse_implication
Parses several implications given as a stringparse_implications
Planets dataplanets
Print Details of Repository Contextsprint_repo_details
Print TikZ Codeprint.tikz_code
Generate Random Formal ContextsRandomContext
Generate a Random Distributive ContextRandomDistributiveContext
Randomize an Existing Formal Contextrandomize_context
Import RuleSet from JSONrules_from_json
R6 class for a Rule SetRuleSet
Save TikZ Code to Filesave_tikz
Scaling RegistryscalingRegistry
GUI to select and download a context from the repositoryselect_repository_context
R6 class for a fuzzy set with sparse internal representationSet
Data for Tourist Destination in Las Vegasvegas