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MAHOUT-876 added build information to README
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Welcome to Apache Mahout!
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Mahout is a scalable machine learning library that implements many different
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approaches to machine learning. The project currently contains implementations
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of algorithms for classification, clustering, genetic programming and
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collaborative filtering, all enabled to scale by leveraging the power of
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Hadoop's Map-Reduce (http://hadoop.apache.org) implementation.
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Mahout is a scalable machine learning library that implements many different
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approaches to machine learning. The project currently contains
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implementations of algorithms for classification, clustering, frequent item
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set mining, genetic programming and collaborative filtering. Mahout is
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scalable along three dimensions: It scales to reasonably large data sets by
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leveraging algorithm properties or implementing versions based on Apache
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Hadoop. It scales to your perferred business case as it is distributed under
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a commercially friendly license. In addition it scales in terms of support
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by providing a vibrant, responsive and diverse community.
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Getting Started
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See https://cwiki.apache.org/MAHOUT/quickstart.html
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To compile the sources run 'mvn clean install'
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To run all the tests run 'mvn test'
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To setup your ide run 'mvn eclipse:eclipse' or 'mvn idea:idea'
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For more info on maven see http://maven.apache.org
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For more information on how to contribute see:
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https://cwiki.apache.org/confluence/display/MAHOUT/How+To+Contribute
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Legal
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Please see the NOTICE.txt included in this directory for more information.

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