SVMlight implementation of Support Vector Machines
SVMlight is an implementation of Support Vector Machines (SVMs) in C. The main features of the program are the following: * fast optimization algorithm
o working set selection based on steepest feasible descent
o "shrinking" heuristic
o caching of kernel evaluations
o 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 variables
* handles many thousands of support vectors
* handles several hundred-thousands of training examples
* supports standard kernel functions and lets you define your own
* uses sparse vector representation
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This page last modified on 2008-07-10
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