Metadata-Version: 1.1
Name: MKLpy
Version: 0.5
Summary: A package for Multiple Kernel Learning scikit-compliant
Home-page: https://github.com/IvanoLauriola/MKLpy
Author: Lauriola Ivano
Author-email: ivano.lauriola@phd.unipd.it
License: GNU General Public License v3.0
Download-URL: https://github.com/IvanoLauriola/MKLpy
Description: MKLpy
        =====
        
        
        **MKLpy** is a framework for Multiple Kernel Learning (MKL)  inspired by the [scikit-learn](http://scikit-learn.org/stable) project.
        
        This package contains:
        * the implementation of some MKL algorithms, such as EasyMKL;
        * tools to operate on kernels, such as normalization, centering, summation, average...;
        * metrics, such as kernel_alignment, radius of Minimum Enclosing Ball, margin between classes, spectral ratio...;
        * kernel functions, including boolean kernels (disjunctive, conjunctive, DNF, CNF) and string kernels (spectrum, fixed length and all subsequences).
        
        
        The documentation of MKLpy is available on [readthedocs.io](https://mklpy.readthedocs.io/en/latest/)!
        
        [![Documentation Status](https://readthedocs.org/projects/mklpy/badge/?version=latest)](https://mklpy.readthedocs.io/en/latest/?badge=latest)
        
        
        Installation
        ------------
        
        **MKLpy** is also available on PyPI:
        ```sh
        pip install MKLpy
        ```
        
        To work properly, **MKLpy** requires:
        
        | Resource     | Website |
        | ------       | ------- |
        | numpy        | [https://www.numpy.org/](https://www.numpy.org/) |
        | PyTorch      | [https://pytorch.org/](https://pytorch.org/) |
        | scikit-learn | [https://scikit-learn.org/stable/](https://scikit-learn.org/stable/) |
        | CVXOPT       | [https://cvxopt.org/](https://cvxopt.org/) |
        
        
        Examples
        --------
        The folder *examples* contains several scripts and snippets of codes to show the potentialities of **MKLpy**. The examples show how to train a classifier, how to process data, and how to use kernel functions.
        
        Additionally, you may read our [tutorials](https://mklpy.readthedocs.io/en/latest/)
        
        
        Work in progress
        ----------------
        **MKLpy** is under development! We are working to integrate several features, including:
        * further MKL algorithms, such as GRAM, MEMO, and SimpleMKL;
        * more kernels for structured data;
        * efficient optimization
        
        
        
        
        Citing MKLpy
        ------------
        If you use MKLpy for a scientific purpose, please cite this library.
        
Keywords: kernel,MKL,learning,multiple kernel learning,EasyMKL,SVM,boolean kernels
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Mathematics
