Algorithm

Philosophy

Association rule learning

Apriori algorithm

GSP Algorithm

Set (abstract data type)

Data mining

Computer science

A priori and a posteriori

Projection (relational algebra)

Algorithm design

Mathematics

Epistemology

Mathematical analysis

Tree (set theory)

Combinatorics

Programming language

The FP-growth algorithm is currently one of the fastest approaches to frequent item set mining. In this paper I describe a C implementation of this algorithm, which contains two variants of the core operation of computing a projection of an FP-tree (the fundamental data structure of the FP-growth algorithm). In addition, projected FP-trees are (optionally) pruned by removing items that have become infrequent due to the projection (an approach that has been called FP-Bonsai). I report experimental results comparing this implementation of the FP-growth algorithm with three other frequent item set mining algorithms I implemented (Apriori, Eclat, and Relim).

An implementation of the FP-growth algorithm