Like Apriori algorithm, FP-Growth is an association rule mining approach. The term FP in the name of this approach, is abbreviation of Frequent Pattern. FP-Growth uses a frequent pattern mining technique to build a tree of frequent patterns (FP-Tree), which can be used to extract association rules. Compared to Apriori, the FP-Growth approach is more efficient and it has better performance for rule mining in large datsets. For more information on the FP-Growth approach, you can refer to the related Wikipedia article, here.
In this post, we are going to share with you, the open-source implementation of FP-Growth association rule mining algorithm in MATLAB. The algorithm is implemented in a structured manner and if you are familiar with MATLAB programming language, you will find it easy, to use the codes in your research projects.
The download link of this project follows.
Implementation of FP-Growth Association Rule Mining in MATLABDownload
Citing This Work
If you wish, you can cite this content as follows.
Cite as:Mostapha Kalami Heris, FP-Growth Association Rule Mining in MATLAB (URL: https://yarpiz.com/98/ypml116-fp-growth), Yarpiz, 2015.