v1.0.0

Profiling - Select with GPU and LAR comparison (#42)

* GPU support - Installation extras of CuPy

* cupy dependencies

* bump hisel version

* Cuda kernels

* Examples and profilers

* Error 137 in tests

* Error 137 in tests

* Files for README

* Profiling - LAR comparison

* Profiling LAR

* New performance bar plot

* update readme

* use cprofile in lar comparison

v0.6.0

Handling of Discrete and Continuous variables - Two kernel types (#40)

* Handling of Discrete and Continuous variables - Two kernel types

* bump version

v0.5.0

Prepare the repo for open-sourcing (#37)

* Prepare the repo for open-sourcing

* Add license

v0.4.0

HISEL v0.4.0 - Better user interface (#35)

* Comprehensive API for selection - to be used in tw-experimentation

* fix hsic search

* categorical tests

* HISEL - v0.4.0 better user interface

v0.3.0

This version contains provides an API in hisel.feature_selection.

v0.2.1

This is the second release of hisel.

It contains the feature selection workflow from pandas dataframes to the selection results. In the workflow, the user can decide to pre-filter features using sklearn.feature_selection.mutual_info_regression.

v0.2.0

This is the second release of hisel.

It contains the feature selection workflow from pandas dataframes to the selection results. In the workflow, the user can decide to pre-filter features using sklearn.feature_selection.mutual_info_regression.

v0.1.0

This is the first release of hisel.
It provides the basic API to perform supervised feature selection through hisel.select.Selector.
The usage is demonstrated in the notebooks/ of the repository.
The release includes two types of kernels, KerneType.RBF and KernelType.DELTA, that are used respectively with FeatureType.CONT and FeatureType.DISCR.