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The SHOGUN machine learning toolbox's focus is on large scale kernel methods and especially on Support Vector Machines (SVM). It comes with a generic interface for SVMs, features several SVM and kernel implementations, includes LinAdd optimizations and also Multiple Kernel Learning algorithms. ... [More] SHOGUN also implements a number of linear methods. It allows the input feature-objects to be dense, sparse or strings and of type int/short/double/char. It provides efficient implementations several kernels but also linear methods, hidden markov models etc. and interfaces to matlab,octave,python,R and has a cmdline interface and allows C++ extensions via a library. [Less]

MATSim is a toolkit for building multi-agent transport simulations.

Twisted Python Experiments and Prototyping for ULS For the past 30-40 years, we as an electronic, networked culture have been building systems of increasing size and complexity. Ultra Large-Scale Systems are the natural descendants of this collective, amalgamated effort, yet they are nascent at ... [More] best. This project is for developing code, tests, experiments, and ultimately, libraries with well-documented APIs useful for the creation of software and and content that can serve as prototypes for ultra large-scale systems. [Less]