About:
Apache Mahout is an Apache Software Foundation project with the goal of creating both a community of users and a scalable, Java-based framework consisting of many machine learning algorithm [...]
Changes:
Apache Mahout introduces a new math environment we call Samsara, for its theme of universal renewal. It reflects a fundamental rethinking of how scalable machine learning algorithms are built and customized. Mahout-Samsara is here to help people create their own math while providing some off-the-shelf algorithm implementations. At its core are general linear algebra and statistical operations along with the data structures to support them. You can use is as a library or customize it in Scala with Mahout-specific extensions that look something like R. Mahout-Samsara comes with an interactive shell that runs distributed operations on a Spark cluster. This make prototyping or task submission much easier and allows users to customize algorithms with a whole new degree of freedom.
Mahout Algorithms include many new implementations built for speed on Mahout-Samsara. They run on Spark 1.3+ and some on H2O, which means as much as a 10x speed increase. You’ll find robust matrix decomposition algorithms as well as a Naive Bayes classifier and collaborative filtering. The new spark-itemsimilarity enables the next generation of cooccurrence recommenders that can use entire user click streams and context in making recommendations.
- Authors:
Apache Software Foundation,
Suneel Marthi,
Isabel Drost,
Ted Dunning,
Grant Ingersoll,
Jake Mannix,
Anand Avati,
Andrew Musselman,
Dmitriy Lyubimov,
Ellen Friedman,
Pat Ferrel,
Sebastian Schelter
- License:
Apache 2.0
- Programming Language:
Java
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- Operating System:
Agnostic
- Data Formats:
Arff,
Lucene,
Mahout Vector,
Various,
Cassandra,
Hbase
- Tags:
Classification,
Clustering,
K Nearest Neighbor Classification,
Genetic Algorithms,
Collaborative Filtering,
Collocations,
Frequent Pattern Mining,
Scalable Singular Value Decomposition,
Svd,
Machine L
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