is.superset: Find Super and Subsets

In arules: Mining Association Rules and Frequent Itemsets

Find Super and Subsets

Description

Provides the generic functions is.subset() and is.superset(), and the methods for finding super or subsets in associations and itemMatrix objects.

Usage

is.superset(x, y = NULL, proper = FALSE, sparse = TRUE, ...)

is.subset(x, y = NULL, proper = FALSE, sparse = TRUE, ...)

## S4 method for signature 'itemMatrix'
is.superset(x, y = NULL, proper = FALSE, sparse = TRUE)

## S4 method for signature 'associations'
is.superset(x, y = NULL, proper = FALSE, sparse = TRUE)

## S4 method for signature 'itemMatrix'
is.subset(x, y = NULL, proper = FALSE, sparse = TRUE)

## S4 method for signature 'associations'
is.subset(x, y = NULL, proper = FALSE, sparse = TRUE)

Arguments

x, y	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 should be returned. Sparse computation requires a significantly smaller amount of memory and is much faster for large sets.
...	currently unused.

Details

Determines 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 are very dense (contain many items).

For rules, the union of lhs and rhs is used a the set of items.

Value

returns a logical matrix or a sparse ngCMatrix 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.

Author(s)

Michael Hahsler and Ian Johnson

See Also

Other postprocessing: is.closed(), is.generator(), is.maximal(), is.redundant(), is.significant()

Other associations functions: abbreviate(), associations-class, c(), duplicated(), extract, inspect(), is.closed(), is.generator(), is.maximal(), is.redundant(), is.significant(), itemsets-class, match(), rules-class, sample(), sets, size(), sort(), unique()

Other itemMatrix and transactions functions: abbreviate(), crossTable(), c(), duplicated(), extract, hierarchy, image(), inspect(), itemFrequencyPlot(), itemFrequency(), itemMatrix-class, match(), merge(), random.transactions(), sample(), sets, size(), supportingTransactions(), tidLists-class, transactions-class, unique()

Examples

data("Adult")
set <- eclat(Adult, parameter = list(supp = 0.8))

### find the supersets of each itemset in set
is.superset(set, set)
is.superset(set, set, sparse = FALSE)

arules documentation built on April 1, 2023, 12:05 a.m.