Nothing

```
library("testthat")
library("arules")
data <- list(
c("a","b","c"),
c("a","b"),
c("a","b","d"),
c("b","e"),
c("a","c"),
c("c","e"),
c("a","b","d","e")
)
names(data) <- paste("Tr",c(1:7), sep = "")
trans <- as(data, "transactions")
context("Rule Induction")
### rules
is <- apriori(trans, parameter=list(supp=0.25, target = "frequent"),
control=list(verb=FALSE))
# inspect(is)
## without transactions
r1 <- ruleInduction(is)
# inspect(r1)
# lhs rhs support confidence lift
#3 {d} => {b} 0.2857143 1.0 1.40
#5 {d} => {a} 0.2857143 1.0 1.40
#9 {b} => {a} 0.5714286 0.8 1.12
#10 {a} => {b} 0.5714286 0.8 1.12
#11 {b,d} => {a} 0.2857143 1.0 1.40
#12 {a,d} => {b} 0.2857143 1.0 1.40
expect_equal(length(r1), 6L)
expect_true(all(quality(r1)$support >= .25))
r2 <- ruleInduction(is, confidence = 1)
# inspect(r2)
# lhs rhs support confidence lift
#3 {d} => {b} 0.2857143 1 1.4
#5 {d} => {a} 0.2857143 1 1.4
#11 {b,d} => {a} 0.2857143 1 1.4
#12 {a,d} => {b} 0.2857143 1 1.4
expect_equal(length(r2), 4L)
expect_true(all(quality(r2)$confidence == 1))
## missing itemsets
is_incomplete <- is[labels(is) != "{a,b}"]
expect_error(r_incomplete <- ruleInduction(is_incomplete),
regex = "cannot induce rules")
## missing support
is_nosupp <- is
# empty quality
quality(is_nosupp) <- data.frame()
expect_error(r_nosupp <- ruleInduction(is_nosupp), regex = "support is missing")
# no support
quality(is_nosupp) <- data.frame(weird_measure = runif(length(is_nosupp)))
# inspect(is_nosupp)
expect_error(r_nosupp <- ruleInduction(is_nosupp), regex = "support is missing")
expect_equal_rules <- function(r1, r2) {
expect_equal(length(r1), length(r2))
r2 <- r2[match(labels(r2), labels(r1))]
expect_equal(labels(r1), labels(r1))
### Note rownames may differ in quality after matching
q1 <- quality(r1)[, c("support", "confidence", "lift")]
rownames(q1) <- NULL
q2 <- quality(r2)[, c("support", "confidence", "lift")]
rownames(q2) <- NULL
expect_equal(q1, q2)
}
## with transactions
r1_w <- ruleInduction(is, transactions = trans)
expect_equal_rules(r1, r1_w)
r2_w <- ruleInduction(is, transactions = trans, confidence =1)
expect_equal_rules(r2, r2_w)
r2_incomplete <- ruleInduction(is_incomplete, transactions = trans)
#> inspect(r2_incomplete)
# lhs rhs support confidence lift itemset
#3 {d} => {b} 0.2857143 1 1.4 7
#5 {d} => {a} 0.2857143 1 1.4 8
#9 {b,d} => {a} 0.2857143 1 1.4 10
#10 {a,d} => {b} 0.2857143 1 1.4 10
expect_equal(length(r2_incomplete), 4)
r2_nosupp <- ruleInduction(is_nosupp, transactions = trans)
expect_equal_rules(r2_nosupp, r1)
## test method apriori and compare to ptree method (default)
## they all need specified transactions
r1_a <- ruleInduction(is, transactions = trans,
control=list(method="apriori"))
expect_equal_rules(r1_a, r1)
r2_a <- ruleInduction(is, transactions = trans,
control=list(method="apriori"), confidence = 1)
expect_equal_rules(r2_a, r2)
# test tidlists
# FIXME: tidlists does not work correctly!
# r1_t <- ruleInduction(is, transactions = trans,
# control=list(method="tidlists"))
# expect_equal_rules(r1_t, r1)
#
# r2_t <- ruleInduction(is, transactions = trans,
# control=list(method="tidlists"), confidence = 1)
# expect_equal_rules(r2_t, r2)
## test with problematic transactions (items have support of 0)
r_t0 <- ruleInduction(is, transactions = trans[0])
expect_equal(length(r_t0), 0L)
r_t2 <- ruleInduction(is, transactions = trans[1:2])
#> inspect(trans[1:2])
# items transactionID
#1 {a,b,c} Tr1
#2 {a,b} Tr2
#> inspect(r_t2)
# lhs rhs support confidence lift itemset
#1 {c} => {a} 0.5 1 1 6
#9 {b} => {a} 1.0 1 1 10
#10 {a} => {b} 1.0 1 1 10
expect_equal(length(r_t2), 3L)
# method apriori
r_t0a <- ruleInduction(is, transactions = trans[0], control=list(method="apriori"))
expect_equal(length(r_t0a), 0L)
r_t2a <- ruleInduction(is, transactions = trans[1:2],
control=list(method="apriori"))
## FIXME: apriori returns rules like {} -> rule induction does not!
expect_equal_rules(r_t2, r_t2a[size(r_t2a)>1])
## test with problematic transactions (items missing, items in different order)
expect_error(ruleInduction(is, transactions = trans[,rev(1:nitems(trans))]),
regex = "Item labels")
expect_error(ruleInduction(is, transactions = trans[,-2]),
regex = "Dimensions")
```

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