imsl.data_mining.frequent_itemsets¶

frequent_itemsets(max_num_products, x, max_set_size=5, min_pct_support=0.1)¶

Compute the frequent itemsets in a transaction set using Apriori.

Parameters:	max_num_products (int) – The maximum number of unique items or products that may be present in the transactions. x ((n, 2) array_like) – An array containing the transaction data. The first column of x contains the transaction IDs, and the second column contains the item IDs. Each row represents a transaction ID and item ID pair. The algorithm assumes that an individual transaction is complete within a single data set. That is, there is no matching of transaction IDs between different data sets. max_set_size (int, optional) – The maximum size of an itemset. Only frequent itemsets with max_set_size or fewer items are considered in the analysis. min_pct_support (float, optional) – The minimum percentage of transactions in which an item or itemset must be present to be considered frequent. min_pct_support must be in the interval [0,1].
Returns:	An object of type `FrequentItemSets` containing the frequent itemsets.
Return type:	FrequentItemSets