Releases: transferwise/hisel
Release list
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.