《SVM-Light》.pdf

SVM-Light Support Vector Machine SVMlight Support Vector Machine Author: Thorsten Joachims thorsten@ Cornell University Department of Computer Science Developed at: University of Dortmund, Informatik, AI-Unit Collaborative Research Center on Complexity Reduction in Multivariate Data (SFB475) Version: 6.02 Date: 14.08.2008 Overview SVMlight is an implementation of Support Vector Machines (SVMs) in C. The main features of the program are the following: fast optimization algorithm working set selection based on steepest feasible descent shrinking heuristic caching of kernel evaluations use of folding in the linear case solves classification and regression problems. For multivariate and structured outputs use SVMstruct . solves ranking problems (e. g. learning retrieval functions in STRIVER search engine). computes XiAlpha-estimates of the error rate, the precision, and the recall efficiently computes Leave-One-Out estimates of the error rate, the precision, and the recall includes algorithm for approximately training large transductive SVMs (TSVMs) (see also Spectral Graph Transducer) can train SVMs with cost models and example dependent costs allows restarts from specified vector of dual varia