[CONF] Apache Mahout > Quickstart

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Space: Apache Mahout (https://cwiki.apache.org/confluence/display/MAHOUT)
Page: Quickstart (https://cwiki.apache.org/confluence/display/MAHOUT/Quickstart)


Edited by Robin Anil:
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h1. Download and Installation

* [Download and installation|BuildingMahout]

h1. Running the Examples

Mahout runs on [Apache Hadoop | http://hadoop.apache.org]. So, to run these examples, install the latest compatible{footnote}When using a release, see the release notes{footnote}{footnote}When using trunk, see _parent/pom.xml_{footnote} [Hadoop Common release | http://hadoop.apache.org/common/]. 

{display-footnotes}

h2. Clustering

* [Synthetic Control Data]


h2. Classification

* [Twenty Newsgroups]
* [Wikipedia Bayes Example]

h2. Genetic Programming

* [Watchmaker|Mahout.GA.Tutorial]

h2. Decision Forest

* [Breiman Example]
* [Partial Implementation]

h2. Recommendation mining

This package comes with four examples based on netflix data, bookcrossing, grouplens and jester data.

* [RecommendationExamples]

h1. Where to Go Next

* If you are working with text, read more on [Creating Vectors from Text]
* To learn more on grouping items by similarity and identifying clusters read more on [Clustering your data|ClusteringYourData]
* If you want to classify incoming items into predefinied categories read more on [Classifying your data |ClassifyingYourData]
* To know how to Mine frequent patterns from your data know how to Mine frequent patterns from your data read more on [Parallel Frequent Pattern Mining|ParallelFrequentPatternMining]
* To read more on building recommendation engines have a look at the [Taste documentation |http://lucene.apache.org/mahout/taste.html] and [Taste hadoop commandline|TasteCommandLine]

Go back to the [Main Wiki Page|http://cwiki.apache.org/MAHOUT] for more information. 



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