Skip to content

An implementation of Passive-Agressive version of SVM algorithm used for online learning

License

Notifications You must be signed in to change notification settings

srikalidindi/Passive-Agressive-SVM-for-online-learning

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Passive-Agressive-SVM-for-online-learning

An implementation of Passive-Agressive version of SVM algorithm used for online learning.

The implementation follows Scikit-Learn API.

This implementation allows to use Kernelized Version of SVM and different optimiation strategies.

Avaliable Kernel Options: linear, rbf, polynomial Avaliable Optimization Strategies:

  • tau = loss / ||X||^2
  • tau = min(c,loss / ||X||^2)
  • tau = loss/(||X||^2 + (1/(2*C)))

About

An implementation of Passive-Agressive version of SVM algorithm used for online learning

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%