Dear all, I am doing experiments as a part of my final project. I'm comparing the performance of Mahout's implementations of recommender algorithms on some public dataset (so far bookcross and grouplens). I want to ask 2 questions:
1. The score (RMSE) results quite vary each time I run an algorithm (sometimes +- 0.5 difference on some algorithms). Is there any way that I can make it produce the same result on each run? Maybe by setting a seed somewhere on the code? Or should I just do like 10 run and take the average score? 2. Where can I see the list of all recommender algorithms already implemented by Mahout? From what I read on Mahout in Action book, there are 6 algorithms: UserBased, ItemBased, Slope One, SVD, KnnItemBased, and TreeClustering. Are there new algorithms since then? Oh, and I found both KnnItem and TreeClustering are deprecated on the newest version of Mahout (0.8-SNAPSHOT) ? Why is this the case? -- Regards, Reinhard Denis Najogie
