Metadata-Version: 2.1
Name: kerch
Version: 0.2
Summary: Python for Kernel Methods
Home-page: https://github.com/hdeplaen/rkm
Author: HENRI DE PLAEN
Author-email: henri.deplaen@esat.kuleuven.be
License: MIT License        
        Copyright (c) 2022 HENRI DE PLAEN        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.        
Project-URL: Documentation, https://hdeplaen.github.io/rkm
Project-URL: Bug Tracker, https://github.com/hdeplaen/rkm/issues
Project-URL: E-DUALITY, https://www.esat.kuleuven.be/stadius/E/
Project-URL: ESAT-STADIUS, https://www.esat.kuleuven.be/stadius/
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: GPU :: NVIDIA CUDA
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: torch (>=1.8)
Requires-Dist: numpy
Requires-Dist: pyyaml
Requires-Dist: tqdm
Requires-Dist: nested-dict
Requires-Dist: hyperopt

# KerPy
[![PyPI version](https://badge.fury.io/py/kerpy.svg)](https://badge.fury.io/py/kerpy)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

KerPy is a Python package meant for various kernel methods, and in particular Deep Restricted Kernel Machines. You can natively perform SVMs, LS-SVMs, (K)PCA with various kernels, automatic centering, out-of-sample, etc.

The package is built on PyTorch and supports GPU acceleration.

<!-- toc -->

[//]: # (* [Examples]&#40;#examples&#41;)

[//]: # (  - [KPCA]&#40;#kernel-principal-component-analysis&#41;)

[//]: # (  - [Large-scale LS-SVM]&#40;#training-a-large-scale-least-squares-support-vector-machine&#41;)

[//]: # (  - [Deep RKM]&#40;#deep-restricted-kernel-machine&#41;)

[//]: # (  - [Recurrent RKM]&#40;#recurrent-restricted-kernel-machines&#41;)
* [Installation](#installation)
  - [PIP](#pip)
  - [From source](#from-source)
* [Acknowledgements](#acknowledgements)
* [Resources](#resources)
* [License](#license)

[//]: # (## Examples)

[//]: # ()
[//]: # (### Kernel Principal Component Analysis)

[//]: # (Example to come...)

[//]: # (### Training a large-scale Least-Squares Support Vector Machine)

[//]: # (Example to come...)

[//]: # (### Deep Restricted Kernel Machine)

[//]: # (Example to come...)

[//]: # (### Recurrent Restricted Kernel Machines )

[//]: # (Example to come...)

## Installation
As for now, there are two ways to install the package.

### PIP
Using pip, it suffices to run `pip install kerpy`. Just rerun this command with the suffix `--upgrade` to upgrade the package to its newest version.

### From source
You can also install the package directly from the GitHub repository.
```
git clone --recursive https://github.com/hdeplaen/kerpy
cd kerpy
python setup.py install
```

## Resources

* [Documentation](https://hdeplaen.github.io/kerpy/)
* [Bug Tracker](https://github.com/hdeplaen/kerpyissues)
* [E-DUALITY](https://www.esat.kuleuven.be/stadius/E/): ERC Adv. Grant website.
* [ESAT-STADIUS](https://www.esat.kuleuven.be/stadius/): KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for
    Dynamical Systems, Signal Processing and Data Analytics.

## Contributors
The contributors and acknowledgements can be found in the [CONRIBUTORS](CONTRIBUTORS) file.

## License
RKM has a MIT license, as found in the [LICENSE](LICENSE) file.
