SHOGUN 1.1.0 Release Machine learning Toolbox

Shogun is a machine learning toolkit that focuses on large kernel methods and support vector Machine (SVM) toolkits. It provides a universal SVM object interface connected to different SVM implementations and efficient kernel implementations. In addition to supporting SVMS and regression analysis, Shogun has some linear methods such as linear discriminant analysis (LDA), linear programming Machine (LPM), (kernel) perceptron and algorithm hidden Markov model. Shogun can be used for c++++, Matlab, R, Octave, and Python.

SHOGUN 1.1.0 This version introduces the concept of "converter", which can build any embedded function. Also included are some new dimensionality reduction techniques and significant performance improvements in dimension reduction kits. Other improvements include an important compile speed, a variety of modular interfaces and algorithmic bug fixes, and improved compatibility of Cygwin, Mac OS X, and clang++. The problem with GitHub is that it is now used to track errors and problems.

Software Information: http://www.shogun-toolbox.org/

Download Address: ftp://shogun-toolbox.org/shogun/releases/1.1/sources/shogun-1.1.0.tar.bz2