Find items frequently purchased with a given item
Value
A tibble of rules involving the specified item, filtered by
min_lift and sorted by lift in descending order.
Examples
# \donttest{
if (requireNamespace("arules", quietly = TRUE)) {
data("Groceries", package = "arules")
res <- tidy_apriori(Groceries, support = 0.001, confidence = 0.5)
find_related_items(res, "whole milk", min_lift = 1.5)
}
#> Apriori
#>
#> Parameter specification:
#> confidence minval smax arem aval originalSupport maxtime support minlen
#> 0.5 0.1 1 none FALSE TRUE 5 0.001 2
#> maxlen target ext
#> 10 rules TRUE
#>
#> Algorithmic control:
#> filter tree heap memopt load sort verbose
#> 0.1 TRUE TRUE FALSE TRUE 2 TRUE
#>
#> Absolute minimum support count: 9
#>
#> set item appearances ...[0 item(s)] done [0.00s].
#> set transactions ...[169 item(s), 9835 transaction(s)] done [0.00s].
#> sorting and recoding items ... [157 item(s)] done [0.00s].
#> creating transaction tree ... done [0.00s].
#> checking subsets of size 1 2 3 4 5 6 done [0.01s].
#> writing ... [5668 rule(s)] done [0.00s].
#> creating S4 object ... done [0.00s].
#> # A tibble: 10 × 8
#> rule_id lhs rhs support confidence coverage lift count
#> <int> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <int>
#> 1 55 {whole milk,Instant fo… {ham… 0.00153 0.5 0.00305 15.0 15
#> 2 5638 {tropical fruit,other … {but… 0.00102 0.625 0.00163 11.3 10
#> 3 5633 {tropical fruit,root v… {bee… 0.00112 0.55 0.00203 10.5 11
#> 4 4734 {tropical fruit,whole … {but… 0.00102 0.556 0.00183 10.0 10
#> 5 1827 {whole milk,whipped/so… {but… 0.00142 0.538 0.00264 9.72 14
#> 6 1826 {whole milk,butter,har… {whi… 0.00142 0.667 0.00214 9.30 14
#> 7 4820 {citrus fruit,other ve… {dom… 0.00112 0.579 0.00193 9.12 11
#> 8 4810 {whole milk,curd,yogur… {whi… 0.00112 0.647 0.00173 9.03 11
#> 9 5044 {other vegetables,whol… {but… 0.00102 0.5 0.00203 9.02 10
#> 10 2699 {citrus fruit,whole mi… {dom… 0.00163 0.571 0.00285 9.01 16
# }