swMATH ID: 45229
Software Authors: Michael Hahsler
Description: ARULESPY: Exploring Association Rules and Frequent Itemsets in Python. 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.
Homepage: https://arxiv.org/abs/2305.15263
Dependencies: Python
Keywords: Databases; arXiv_cs.DB; Association Rules; association rule mining; Python
Related Software: ggplot2; htmlwidgets; RPy; UCI-ml; visNetwork; plotly; rpy2; Matrix; MLxtend; arulesViz; arules; Python
Cited in: 0 Documents

Standard Articles

1 Publication describing the Software Year
ARULESPY: Exploring Association Rules and Frequent Itemsets in Python arXiv
Michael Hahsler