debug <- FALSE data("Adult") ## Mine association rules. rules <- apriori(Adult, parameter = list( supp = 0.5, conf = 0.9, target = "rules" ), control = list(verb = FALSE)) measures <- c("count", "confidence", "lift", "oddsRatio", "phi", "support") # smooth = .5 is Haldane-Anscombe correction for (m in measures) { if (debug) cat("CI for", m, "\n") ci <- cbind(measure = interestMeasure(rules, m, smooth = .5), confint(rules, m)) if (debug) print(ci) expect_false(any(ci[,1] < ci[,2] | ci[,1] > ci[,3] | ci[,2] > ci[,3], na.rm = TRUE), info = m) } # exact intervals should be tighter #confint(rules, "oddsRatio_normal") - confint(rules, "oddsRatio") #confint(rules, "support_normal") - confint(rules, "support") #confint(rules, "confidence_normal") - confint(rules, "confidence") #ci <- confint(rules, "confidence") #ci <- confint(rules, "support") #ci[,2] - ci[,1] # is.significant s <- is.significant(rules, method = "Fisher", alpha = 0.05, adjust = "none") s2 <- interestMeasure(rules, "Fisher") <= 0.05 expect_equal(s, s2)