FP-growth is a program to find frequent item sets (also closed and maximal as well as generators) with the FP-growth algorithm (Frequent Pattern growth [Han et al. 2000]), which represents the transaction database as a prefix tree which is enhanced with links that organize the nodes into lists referring to the same item. The search is carried out by projecting the prefix tree, working recursively on the result, and pruning the original tree. The implementation also supports filtering for closed and maximal item sets with conditional item set repositories as suggested in [Grahne and Zhu 2003], although the approach used in the program differs in as far as it used top-down prefix trees rather than FP-trees. It does not cover the clever implementation of FP-trees with two integer arrays as suggested in [Rasz 2004]. Since version 6.0 the program made available above can also be used to find association rules.
Keywords for this software
References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Wang, Tong; Rudin, Cynthia; Doshi-Velez, Finale; Liu, Yimin; Klampfl, Erica; Macneille, Perry: A Bayesian framework for learning rule sets for interpretable classification (2017)
- Letham, Benjamin; Rudin, Cynthia; McCormick, Tyler H.; Madigan, David: Interpretable classifiers using rules and Bayesian analysis: building a better stroke prediction model (2015)
- Letham, Benjamin; Rudin, Cynthia; Madigan, David: Sequential event prediction (2013)