The project requires the implementation of FP-growth algorithm in Java [Han, Pei & Yin 2000]. In addition to implementation of the standard algorithm, ten different correlation measures will be selected from the attached presentation (Slide 25) and the algorithm should be workable with these correlation measures, as well. The results will be tested on a data set (with at least 10000 records) from UCI Machine learning repository. The algorithm has to be proven for small benchmark data first. The implementations will be in JAVA or C# and to be informed in case of partial or complete use of other codes from Internet.
The project has to be completed within 2 weeks.