I am a part-time graduate student currently taking a data mining course and am looking to potentially contribute to Mahout as a class project. I've noticed there are a few algorithms on the Algorithms wiki page that have yet to be implemented, such as Locally Weighted Linear Regression, Principal Components Analysis, Independent Component Analysis, and Gaussian Discriminative Analysis. As I'm new to these algorithms and machine learning in general I am seeking advice on which of these (if any) would be suitable to take on given a limited amount of time (a little over 2 months, juggled with a full-time job) and background knowledge. I have worked with Hadoop for over a year now and do have several years of Java experience. Any other suggestions would be welcome as well.
Thanks.
