amccarren / ms-apriori

MS-Apriori is used for frequent item set mining and association rule learning over transactional data.

MS-Apriori

MS-Apriori is an extended version of Apriori to allow multiple minimum supports. In this the minimum support of a rule is expressed in terms of minimum item supports (MIS) of the items that appear in the rule. That is, each item in the data can have a MIS value specified by the user. By providing different MIS values for different items, the user effectively expresses different support requirements for different rules. Like Apriori, MS-Apriori is also based on level-wise search. It generates all frequent itemsets by making multiple passes over the data.

Usage

python msapriori.py transaction_file parameter_file output_file

Credits

Dr. Bing Liu