SHOGUN SHOGUN is a machine learning toolbox.
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machine machine learning scale scale machine Vector Machines SHOGUN

SHOGUN Description

SHOGUN is a machine learning toolbox. SHOGUN is a machine learning toolbox whose focus is on large scale kernel methods and especially on Support Vector Machines (SVM). The project provides a generic SVM object interfacing to several different SVM implementations, all making use of the same underlying, efficient kernel implementations.Apart from SVMs and regression, SHOGUN also features a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons, and algorithms to train hidden Markov models. SHOGUN can be used from within C++, Matlab, R, Octave, and Python. What's New in This Release: · This release contains a quite large number of bugfixes documentation updates (tutorials and a method overview are now available for C++ developers, with static and modular interfaces). · Multiple Kernel Learning has been reworked, and works using interleaved optimization via SVMLight or the wrapper algorithm via any SVM like LibSVM for regression and one and two-class classification.

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