associations or itemMatrix objects. If y = NULL,
the super or subset structure within set x is calculated.
proper
a logical indicating if all or just proper super or subsets.
sparse
a logical indicating if a sparse (ngCMatrix) rather than a
dense logical matrix sgould be returned. Sparse computation
preserves a significant amount of memory and is much faster for large sets.
…
currently unused.
Value
returns a logical matrix
or a sparse ngCMatrix (for sparse=TRUE)
with length(x) rows and length(y)
columns. Each logical row vector represents which elements in y are
supersets (subsets) of the corresponding element in x. If either
x or y have length zero, NULL is returned instead of a
matrix.
Details
looks for each element in x which elements in y are supersets or
subsets. Note that the method can be very slow and memory intensive if
x and/or y contain many elements.
For rules, the union of lhs and rhs is used a the set of items.
# NOT RUN {data("Adult")
set <- eclat(Adult, parameter = list(supp = 0.8))
### find the supersets of each itemset in setis.superset(set, set)
is.superset(set, set, sparse = FALSE)
# }