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LIBSVMTL - a Support Vector Machine Template Library
LIBSVMTL is a highly customizable C++ Support Vector Machine library based on Chih-Jen Lin's LIBSVM. The goals of splitting the library into template classes were:
- let user decide wether to use sparse or dense storage for feature vectors
- easier extention with new algorithms via a more object oriented design, e.g. in libsvmTL one kernel (which is the kernel function, its name, commandline parameters, loading/saving its parameters, description of commandline parameters) is represented by one object. Same for two-class and multi-class algorithms
- integration into own programs (e.g., using own FeatureVector classes, using your own data file format, etc.)
- easier development and maintainance of interfaces to higher level languages (e.g. matlab, python, etc)
- making the library parts as independent as possible, to allow multiple developers to contribute
- speed improvements
Besides that, the low-level training algorithms and structure is as identical to original libsvm from Chih-Jen-Lin as possible (only some minor changes to include the templated feature vectors and kernel functions), which allows easy integration of further improvements in libsvm and ensures correct numerics.