Mahout

Apache Mahout is a highly optimised library of machine learning and data mining algorithms, built for scalability. Use cases include Recommendation mining, Clustering, Classification and Frequent itemset mining.

The algorithms are implemented using the 'map-reduce' paradigm, which enables the computations to be distributed across a cluster of computers (such as a Hadoop cluster), though Mahout can also be (and is usually initially) deployed on a single machine. The project aims to create and connect a vibrant community of developers and machine learning enthusiasts.

 

Category: 
Text mining
Availability: 
Offline
Other software required: 
Other software required
Difficulty: 
Advanced
User Community: 
Mailing lists and IRC channel.
Active Development: 
Active development
Purpose: 
Single purpose
Operating System: 
Windows
Operating System: 
Mac
Operating System: 
Unix
System Requirements: 
Designed to run on Apache's Hadoop platform, although it can run on a non-Hadoop cluster.