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#######################################################################
# arules - Mining Association Rules and Frequent Itemsets
# Copyright (C) 2011-2015 Michael Hahsler, Christian Buchta,
# Bettina Gruen and Kurt Hornik
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License along
# with this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
#' Find Closed Itemsets
#'
#' Provides the generic function and the method `is.closed()` for finding
#' closed itemsets.
#' Closed itemsets are used as a concise representation of
#' frequent itemsets. The closure of an itemset is its largest proper superset
#' which has the same support (is contained in exactly the same transactions).
#' An itemset is closed, if it is its own closure (Pasquier et al. 1999).
#'
#' Closed frequent itemsets can also be mined directly using
#' [apriori()] or [eclat()] with target `"closed frequent
#' itemsets"`.
#'
#' @aliases is.closed
#' @family postprocessing
#' @family associations functions
#'
#' @param x a set of itemsets.
#'
#' @return a logical vector with the same length as `x` indicating for
#' each element in `x` if it is a closed itemset.
#' @author Michael Hahsler
#' @references
#' Nicolas Pasquier, Yves Bastide, Rafik Taouil, and Lotfi Lakhal
#' (1999). Discovering frequent closed itemsets for association rules. In
#' _Proceeding of the 7th International Conference on Database Theory_,
#' Lecture Notes In Computer Science (LNCS 1540), pages 398--416. Springer,
#' 1999.
#' @keywords models
setGeneric("is.closed",
function(x)
standardGeneric("is.closed"))
#' @rdname is.closed
setMethod("is.closed", signature(x = "itemsets"),
function(x) {
## An itemset X is closed if no proper super set of X is contained
## in every transaction in which X is contained. Which means there
## exists no super set of X with the same support count as X
## Check if the set of itemsets is unique in order to
## avoid the problem that the same itemset could have
## different support counts.
if (any(is.na(match(x, unique(x), nomatch = NA))))
stop("itemsets not unique")
## R_pnclosed only supports abs. support counts
cnt <- quality(x)$count
if (is.null(cnt)) {
ntrans <- info(x)$ntransactions
if (is.null(ntrans))
stop(
sQuote("x"),
" does not contain sufficient support information (ntransations is missing in info)"
)
supp <- quality(x)$support
if (is.null(supp))
stop(
sQuote("x"),
" does not contain sufficient support information (support is missing in quality)"
)
cnt <- as.integer(round(supp * ntrans))
}
structure(.Call(R_pnclosed, x@items@data, as.integer(cnt), FALSE),
names = labels(x))
})
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