Implementation of Association Rule Mining Algorithm: Apriori Algorithm

This document presents a MATLAB implementation of the Apriori algorithm for association rule mining, which automatically generates association rules while calculating support and confidence metrics. The Apriori algorithm is a widely-used association rule mining technique that efficiently discovers frequent itemsets from datasets and generates corresponding association rules. Through MATLAB implementation, users can conveniently execute the algorithm and analyze results with built-in functions for itemset generation and statistical calculations. The implementation typically includes key components such as candidate itemset generation using join operations, support counting through database scans, and pruning strategies to eliminate infrequent subsets. By leveraging this MATLAB implementation, researchers can conduct more in-depth studies in association rule mining and obtain more accurate and comprehensive results through customizable parameters and visualization tools.