smo.h File Reference

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Variables
const double	ID_FREE = 0
const double	ID_LOWER_BOUNDED = -1
const double	ID_UPPER_BOUNDED = 1
const index_t	MAX_NUM_ITER = 10000
const index_t	NUM_FOR_SHRINKING = 1000
const double	SMO_ALPHA_ZERO = 1.0e-4
const double	SMO_OPT_TOLERANCE = 1.0e-4
const double	SMO_UNSHRINKING_TOLERANCE = 10 * SMO_OPT_TOLERANCE
const double	TAU = 1e-12

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Detailed Description

Author:

Hua Ouyang

This head file contains functions for performing Sequential Minimal Optimization (SMO)

The algorithms in the following papers are implemented:

1. SMO and Working set selecting using 1st order expansion {Platt_SMO, author = "J. C. Platt", title = "{Fast Training of Support Vector Machines using Sequential Minimal Optimization}", booktitle = "{Advances in Kernel Methods - Support Vector Learning}", year = 1999, publisher = "MIT Press" }

2. Shrinkng and Caching for SMO {Joachims_SVMLIGHT, author = "T. Joachims", title = "{Making large-Scale SVM Learning Practical}", booktitle = "{Advances in Kernel Methods - Support Vector Learning}", year = 1999, publisher = "MIT Press" }

3. Working set selecting using 2nd order expansion {Fan_JMLR, author = "R. Fan, P. Chen, C. Lin", title = "{Working Set Selection using Second Order Information for Training Support Vector Machines}", journal = "{Jornal of Machine Learning Research}", year = 2005 }

4. TODO: budget L2 SVM {Budge_SVM, author = "O. Dekel and Y. Singer", title = "{Support Vector Machines on a Budget}", booktitle = NIPS, number = 19, year = 2006 }

See also:

svm.h

Definition in file smo.h.