Here’s the announcement:

Apache Mahout <> 0.3 has been released and is
now available for public
download at

Up-to-date maven artifacts can be found in the Apache repository at

Apache Mahout is a subproject of Apache Lucene with the goal of
delivering scalable machine learning algorithm implementations under
the Apache license.

Mahout is a machine learning library meant to scale: Scale in terms of
community to support anyone interested in using machine learning.
Scale in terms of business by providing the library under a
commercially friendly, free software license. Scale in terms of
computation to the size of data we manage today.

Built on top of the powerful map/reduce paradigm of the Apache Hadoop
project, Mahout lets you solve popular machine learning problem
settings like clustering, collaborative filtering and classification
over Terabytes of data over thousands of computers.

Implemented with scalability in mind the latest release brings many
performance optimizations so that even in a single node setup the
library performs well.

The complete changelist can be found here:

New Mahout 0.3 features include:

* New math and collections modules based on the high performance Colt
* Faster Frequent Pattern Growth (FPGrowth) using FP-bonsai pruning
* Parallel Dirichlet process clustering (a model-based clustering
* Parallel co-occurrence based recommender
* Parallel text document to vector conversion using LLR based ngram
* Parallel Lanczos SVD (Singular Value Decomposition) solver
* Shell scripts for easier running of algorithms, utilities and examples
* …and much much more: code cleanup, many bug fixes and
performance improvements

Getting started: New to Mahout?

* Download Mahout at
* Check out the Quick start:
* Read the Mahout Wiki:
* Join the community by subscribing to
* Give back:
* Consider adding yourself to the power by Wiki

For more information on Apache Mahout, see