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From Grant Ingersoll <gsing...@apache.org>
Subject [ANNOUNCE] Apache Mahout 0.1 Released
Date Tue, 07 Apr 2009 20:08:05 GMT
The Apache Lucene project is pleased to announce the release of Apache  
Mahout 0.1.
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.

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 (http://hadoop.apache.org 
) for scalability

The release contents have been pushed out to the main Apache release
site and the m2 ibiblio sync repository.

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 JIRA:


Apache Mahout is available in source form from the following download  

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  
using signatures found on the Apache site:

For more information on Apache Mahout, visit the project home page:
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