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 1 weeks.
I have experience working as a research Java programmer and a enterprise J2EE software engineer. Being a PhD student I am comfortable with reading research papers and implementing them. I would like to help you out.
Hi! I can write the FP-growth algorithm in JAVA. And on slide 25 there are about 23 corelation measures, which 10 do you want to use? And from the UCI repository can I use any dataset having more that 10k records? Thank you!