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A framework for learning from a continuous supply of examples, a data stream. Includes classification, regression, clustering, outlier detection and recommender systems. Related to the WEKA project, also written in Java, while scaling to adaptive large scale machine learning.
sparse and dense matrix, linear algebra, visualization, big data
The Universal Java Matrix Package (UJMP) is an open source Java library which provides sparse and dense matrix classes, as well as a large number of calculations for linear algebra such as matrix multiplication or matrix inverse. Operations such as mean, correlation, standard deviation, replacement of missing values or the calculation of mutual information are supported, too.
The Universal Java Matrix Package provides various visualization methods, import and export filters for a large...
PMML-compliant scoring engine and analytic toolkit
Augustus development has moved to google code. The new project page is augustus.googlecode.com. New releases of the project are not currently being released to sourceforge.
Augustus is designed for statistical and data mining models and produces and consumes models with 10,000s of segments.
Versions of Augustus support PMML 3, 4.0.1, and 4.1.