Map-reduce machine learning: Mahout 0.1 Release

Grant announced on his blog the release of Apache Mahout 0.1. Mahout is an effort to port several standard machine learning algorithms to the Hadoop map-reduce framework.

Grant gives an update on the algorithms integrated so far:

We have several clustering algorithm implementations: k-Means, fuzzy k-Means, Dirichlet, Mean-Shift, Canopy. We also have implementations of naive bayes and complementary naive bayes for classification and some integration with the Watchmaker evolutionary programming framework.

The webpage should be updated with the link to the release shortly.

You can also check out Grant's slides from ApacheCon and the Mahout Wiki.