The Apache Lucene project is pleased to announce the release of Apache Mahout 0.1. Apache Mahout is a sub project 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. Highlights include: 1. Taste Collaborative Filtering 2. Several distributed clustering implementations: k-Means, Fuzzy k-Means, Dirchlet, Mean-Shift and Canopy 3. Distributed Naive Bayes and Complementary Naive Bayes classification implementations 4. Distributed fitness function implementation for the Watchmaker evolutionary programming library 5. Most implementations are built on top of Apache Hadoop ( for scalability Apache Mahout 0.1 is the project's first release and is focused on establishing a baseline release while attracting more contributors. Details can be found in Apache's issue tracker: Apache Mahout is available in source form from the following download page: Apache Mahout is also available for Maven 2 users via the Central Maven Repositories: When downloading from a mirror site, please remember to verify the downloads using signatures found on the Apache site: For more information on Apache Mahout, visit the project home page: