Formal Concept Analysis (FCA) connects data analysis with Order Theory and Lattice Theory. Beyond simply extracting concepts, it is often useful to analyze the algebraic structure of the resulting Concept Lattice.
This vignette introduces a new set of features in fcaR,
Algebraic Properties: Efficiently check if a concept
lattice is distributive, modular, semimodular, or atomic.
The ConceptLattice class now provides methods to verify
standard lattice-theoretic properties. These checks are implemented in
optimized C++ for performance.
Let’s use the built-in planets dataset as an
example:
fc <- FormalContext$new(planets)
fc$find_concepts()
# Check properties
print(paste("Is Distributive?", fc$concepts$is_distributive()))
#> [1] "Is Distributive? FALSE"
print(paste("Is Modular?", fc$concepts$is_modular()))
#> [1] "Is Modular? FALSE"
print(paste("Is Semimodular?", fc$concepts$is_semimodular()))
#> 'as(<ngCMatrix>, "dgCMatrix")' is deprecated.
#> Use 'as(., "dMatrix")' instead.
#> See help("Deprecated") and help("Matrix-deprecated").
#> [1] "Is Semimodular? FALSE"
print(paste("Is Atomic?", fc$concepts$is_atomic()))
#> [1] "Is Atomic? TRUE"The “Diamond” lattice (\(M_3\)) is the smallest non-distributive lattice. Let’s create it manually to verify our checks.
# Context for M3 (The Diamond)
# 3 objects, 3 attributes. Objects have 2 attributes each.
I_m3 <- matrix(c(
0, 1, 1,
1, 0, 1,
1, 1, 0
), nrow = 3, byrow = TRUE)
fc_m3 <- FormalContext$new(I_m3)
fc_m3$find_concepts()
# M3 is Modular but NOT Distributive
print(paste("M3 Distributive:", fc_m3$concepts$is_distributive()))
#> [1] "M3 Distributive: TRUE"
print(paste("M3 Modular:", fc_m3$concepts$is_modular()))
#> [1] "M3 Modular: TRUE"