Apache Mahout is a subproject of Apache Lucene with the goal of delivering scalable machine learning algorithm implementations under the Apache license. The first public release includes implementations for clustering, classification, collaborative filtering and evolutionary programming.
* Taste Collaborative Filtering
* Several distributed clustering implementations: k-Means, Fuzzy k-Means, Dirchlet, Mean-Shift and Canopy
* Distributed Naive Bayes and Complementary Naive Bayes classification implementations
* Distributed fitness function implementation for the Watchmaker evolutionary programming library
* Most implementations are built on top of Apache Hadoop (http://hadoop.apache.org) for scalability
links for 2009-04-25