Skip to content

Conformal prediction is a framework for providing accuracy guarantees on the predictions of a base predictor

License

Notifications You must be signed in to change notification settings

koulanurag/conformal

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

12 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Conformal Prediction

Conformal prediction is a framework for providing accuracy guarantees on the predictions of a base predictor.

[Status: No Longer Maintained | Code provided as it is]

Installation

Conformal uses the following dependencies:

  • numpy,
  • pyyaml
  • HDF5 and h5py (optional, required if you use model saving/loading functions)

To install Conformal, cd to the conformal folder and run the install command:

python setup.py install

Usage

cf = ConformalPrediction(model_prediction, Y_test, 5, measure=SoftMax(), threshold_mode=0)
cf_prediction = cf.predict(model_prediction)
cf_accuracy = cf.evaluate(cf_prediction, Y_test)

Please refer here for more usage details.

Contributing

  1. Fork it!
  2. Create your feature branch: git checkout -b my-new-feature
  3. Commit your changes: git commit -am 'Add some feature'
  4. Push to the branch: git push origin my-new-feature
  5. Submit a pull request :D

References:

  1. http://ieeexplore.ieee.org/document/4410411/

About

Conformal prediction is a framework for providing accuracy guarantees on the predictions of a base predictor

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages