{ "info": { "author": "Lauriola Ivano", "author_email": "ivano.lauriola@phd.unipd.it", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Programming Language :: Python :: 3.6", "Topic :: Scientific/Engineering :: Artificial Intelligence", "Topic :: Scientific/Engineering :: Mathematics" ], "description": "MKLpy\n=====\n\n\n**MKLpy** is a framework for Multiple Kernel Learning (MKL) inspired by the [scikit-learn](http://scikit-learn.org/stable) project.\n\nThis package contains:\n* the implementation of some MKL algorithms, such as EasyMKL;\n* tools to operate on kernels, such as normalization, centering, summation, average...;\n* metrics, such as kernel_alignment, radius of Minimum Enclosing Ball, margin between classes, spectral ratio...;\n* kernel functions, including boolean kernels (disjunctive, conjunctive, DNF, CNF) and string kernels (spectrum, fixed length and all subsequences).\n\nThe 'examples' folder contains useful snippets of code.\n\n\n\nInstallation\n------------\n\n**MKLpy** is also available on PyPI:\n```sh\npip install MKLpy\n```\n\nTo work properly, **MKLpy** requires:\n\n| resource | website |\n| ------ | ------ |\n| numpy | [https://www.numpy.org/](https://www.numpy.org/) |\n| scikit-learn | [https://scikit-learn.org/stable/](https://scikit-learn.org/stable/) |\n| cvxopt | [https://cvxopt.org/](https://cvxopt.org/) |\n\n\nExamples\n--------\nThe folder *examples* contains several scripts and snippets of codes to show the potentialities of **MKLpy**. 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