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#######################################################################
# arulesViz - Visualizing Association Rules and Frequent Itemsets
# Copyrigth (C) 2011 Michael Hahsler and Sudheer Chelluboina
#
# 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.
.get_parameters <- function(p, parameter) {
if(!is.null(parameter) && length(parameter) != 0) {
# get rid of NULL enties
parameter[sapply(parameter, is.null)] <- NULL
o <- pmatch(names(parameter), names(p))
if(any(is.na(o)))
stop(sprintf(ngettext(length(is.na(o)),
"Unknown option: %s",
"Unknown options: %s"),
paste(names(parameter)[is.na(o)],
collapse = " ")))
p[o] <- parameter
}
p
}
rulesAsDataFrame <- function(rules, measure = "support") {
antes <- labels(lhs(rules))$elements
conseqs <- labels(rhs(rules))$elements
data.frame(
antecedent = ordered(antes, levels = unique(antes)),
consequent = ordered(conseqs, level = unique(conseqs)),
measure = quality(rules)[[measure]]
)
}
rulesAsMatrix <- function(rules, measure = "support") {
df <- rulesAsDataFrame(rules, measure)
antes <- as.integer(df$antecedent)
conseqs <- as.integer(df$consequent)
m <- matrix(NA,
ncol = length(unique(antes)), nrow = length(unique(conseqs)))
dimnames(m) <- list(levels(df$consequent), levels(df$antecedent))
enc <- m
for (i in 1:nrow(df)) {
m[conseqs[i], antes[i]] <- df$measure[i]
enc[conseqs[i], antes[i]] <- i
}
attr(m, "encoding") <- enc
m
}
rulesAStable <- function(rules, data) {
tables <- list()
for (i in 1:length(rules)) {
tables[[i]] <- getTable(rules[i], data)
}
tables
}
getTable <- function(rule, data) {
antecedent <- unlist(LIST(lhs(rule), decode = FALSE))
consequent <- unlist(LIST(rhs(rule), decode = FALSE))
transactions <- data[, c(antecedent, consequent)]
ruleAsDataFrame <- as.data.frame(as(transactions, "matrix"))
for (i in 1:ncol(ruleAsDataFrame)) {
ruleAsDataFrame[[i]] <- factor(ruleAsDataFrame[[i]],
levels = c(0, 1), labels = c("no", "yes"))
}
table(ruleAsDataFrame)
}
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