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Logo streamDM 0.0.1

by abifet - April 28, 2015, 12:34:00 CET [ Project Homepage BibTeX Download ] 7596 views, 2133 downloads, 0 subscriptions

About: streamDM is a new open source data mining and machine learning library, designed on top of Spark Streaming, an extension of the core Spark API that enables scalable, high-throughput, fault-tolerant stream processing of data streams.

Changes:

Initial Announcement on mloss.org.

Logo JMLR MOA Massive Online Analysis Nov-13

by abifet - April 4, 2014, 03:50:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 37688 views, 10423 downloads, 0 subscriptions

About: Massive Online Analysis (MOA) is a real time analytic tool for data streams. It is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA includes a collection of offline and online methods as well as tools for evaluation. In particular, it implements boosting, bagging, and Hoeffding Trees, all with and without Naive Bayes classifiers at the leaves. MOA supports bi-directional interaction with WEKA, the Waikato Environment for Knowledge Analysis, and it is released under the GNU GPL license.

Changes:

New version November 2013

Logo SAMOA 0.0.1

by gdfm - April 2, 2014, 17:09:08 CET [ Project Homepage BibTeX Download ] 7104 views, 2114 downloads, 0 subscriptions

About: SAMOA is a platform for mining big data streams. It is a distributed streaming machine learning (ML) framework that contains a programing abstraction for distributed streaming ML algorithms.

Changes:

Initial Announcement on mloss.org.