`ARules.apriori`

— Methodapriori(occurrences, item_lkup; supp, conf, maxlen)

Given an boolean occurrence matrix of transactions (rows are transactions, columns are items) and a lookup dictionary of column-index to items-string, this function runs the a-priori algorithm for generating frequent item sets. These frequent items are then used to generate association rules. The `supp`

argument allows us to stipulate the minimum support required for an itemset to be considered frequent. The `conf`

argument allows us to exclude association rules without at least `conf`

level of confidence. The `maxlen`

argument stipulates the maximum length of an association rule (i.e., total items on left- and right-hand sides)

`ARules.apriori`

— Method`apriori(transactions; supp, conf, maxlen)`

Given an array of transactions (a vector of string vectors), this function runs the a-priori algorithm for generating frequent item sets. These frequent items are then used to generate association rules. The `supp`

argument allows us to stipulate the minimum support required for an itemset to be considered frequent. The `conf`

argument allows us to exclude association rules without at least `conf`

level of confidence. The `maxlen`

argument stipulates the maximum length of an association rule (i.e., total items on left- and right-hand sides)

`ARules.frequent`

— Method`frequent()`

This function just acts as a bit of a convenience function that returns the frequent item sets and their support count (integer) when given and array of transactions. It basically just wraps frequent*item*tree() but gives back the plain text of the items, rather than that Int16 representation.

`ARules.frequent_item_tree`

— Methodfrequent*item*tree(occurrences, minsupp, maxdepth)

This function creates a frequent itemset tree from an occurrence matrix. The tree is built recursively using calls to the growtree!() function. The `minsupp`

and `maxdepth`

parameters control the minimum support needed for an itemset to be called "frequent", and the max depth of the tree, respectively

`ARules.frequent_item_tree`

— Method`frequent_item_tree(transactions, minsupp, maxdepth)`

This function creates a frequent itemset tree from an array of transactions. The tree is built recursively using calls to the growtree!() function. The `minsupp`

and `maxdepth`

parameters control the minimum support needed for an itemset to be called "frequent", and the max depth of the tree, respectively