Skip to content

Implemeting SVM to classify images with hinge loss and the softmax loss.

Notifications You must be signed in to change notification settings

chandra447/SVM-Image-classifier

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 

Repository files navigation

SVM-Image-classifier

  • The work demonstrates the image classification with both the hinge loss and the softmax loss with better explanation of the mathematics behind.
  • For the demonstration we are using the CIFAR-10 dataset to classify the images and we compare the accuaracy for thse 2 losses and also the work demonstrates the pros and cons of these 2 different losses.
  • To download the dataset to your local machine run the bash file on get_datasets.sh or you can download from the reference link in the notebook attached.
  • Hope this work gives a great intution about SVM(Support Vector Machines) considering different losses.
  • The work is implented only using basic libraries such as numpy but not using any other high level API's.

About

Implemeting SVM to classify images with hinge loss and the softmax loss.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published