A Java Toolbox for Analysis of MassIve Data STreams using Probabilistic Graphical Models
Andrés R. Masegosa, Martinez, Ana Maria, Darío Ramos-López, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Rafael Cabañas, Anders Læsø Madsen · VBN Forskningsportal (Aalborg Universitet) · 2016
Description: • Analysis of big data streams: A complete collection of algorithms for inference and learning of both static and dynamic Bayesian networks from streaming data. Existing software systems for PGMs only focus on stationary datasets. • Distributed parallel algorithms: AMIDST provides parallel multi-core and distributed implementations of Bayesian parameter learning, using streaming variational Bayes and variational message passing.