An Implementation of FP-Growth Algorithm Based on High Level Data Structures of Weka-JUNG Framework

Abstract

FP-Growth is a classical data mining algorithm; most of its current implementations are based on programming language's primitive data types for their data structures; this leads to poor readability & reusability of the codes. Weka is an open source platform for data mining, but lacks of the ability in dealing with tree-structured data; JUNG is a network/graph computation framework. Starting from the analysis on Weka's foundation classes, builds a concise implementation for FP-Growth algorithm based on high level object-oriented data objects of the Weka-JUNG framework; comparison experiments against Weka's built-in Apriori implementation are carried out and its correctness is verified. This implementation has been published as an open source Google Code project.