2023/05/24 by Michael Hahsler, Hahsler, Michael · 1 citation
Computer Science · #Data Mining Algorithms and Applications #Databases (cs.DB) #FOS: Computer and information sciences
paper · pdf · doi:10.48550/arxiv.2305.15263
openalex publication_date 2023/05/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The R arules package implements a comprehensive infrastructure for representing, manipulating, and analyzing transaction data and patterns using frequent itemsets and association rules. The package also provides a wide range of interest measures and mining algorithms, including the code of Christian Borgelt's popular and efficient C implementations of the association mining algorithms Apriori and Eclat, and optimized C/C++ code for mining and manipulating association rules using sparse matrix representation. This document describes the new Python package arulespy, which makes this infrastructure available for Python users.