Fast Intersection / Additive Kernel SVMs
Alexander C. Berg and
Below is a C++/MATLAB implementation of the fast Intersection Kernel
SVM classifier described in the paper:
Classification Using Intersection Kernel Support Vector Machines is efficient.
Subhransu Maji and Alexander C. Berg and Jitendra Malik.
In Proceedings, CVPR 2008, Anchorage, Alaska.
The source code is available as a tar.gz
- (2/2/11) fast-additive-svms.tar.gz | README
- Includes libsvm-mat-3.0-1 : latest version of LIBSVM at the time of release.
- Support for learning models using the intersection, chisquared, and JS kernel.
- Fast approximate classification for these kernels using piecewise linear approximations. ONLY piecewise linear approximations are supported. The binary search based exact classification
for intersection kernel is no longer supported.
- C/C++ based mex code for picewise linear interpolation, weighted kernel sampling and a fast binary search based
weighted intersection kernel sampling.
- Support for float/double features.
- Precomputation and prediction are now separate modules. Lightweight approximate models can be
precomputed and stored without the need to store all the support
- Approximate(or exact) predictions can be done directly using the
approximate(or exact) precomputed models.
- Check out the README/READMEFAST for documentation.
- (05/19/08) libsvm-mat-2.8.1-fast.tar.gz