https://github.com/rushter/heamy

A set of useful tools for competitive data science.
https://github.com/rushter/heamy

data-science machine-learning stacking

Last synced: about 1 month ago
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A set of useful tools for competitive data science.

• Host: GitHub
• URL: https://github.com/rushter/heamy
• Owner: rushter
• License: mit
• Created: 2016-05-12T12:42:10.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2022-12-08T05:05:51.000Z (almost 2 years ago)
• Last Synced: 2024-06-20T22:31:57.273Z (3 months ago)
• Topics: data-science, machine-learning, stacking
• Language: Python
• Homepage: http://heamy.readthedocs.io/en/latest/
• Size: 89.8 KB
• Stars: 551
• Watchers: 16
• Forks: 114
• Open Issues: 8
• Metadata Files:
  • Readme: README.rst
  • Contributing: CONTRIBUTING.rst
  • License: LICENSE

Awesome Lists containing this project

README

        
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heamy

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.. image:: https://img.shields.io/pypi/v/heamy.svg

        :target: https://pypi.python.org/pypi/heamy

.. image:: https://img.shields.io/travis/rushter/heamy.svg

        :target: https://travis-ci.org/rushter/heamy

.. image:: https://coveralls.io/repos/github/rushter/heamy/badge.svg?branch=master

        :target: https://coveralls.io/github/rushter/heamy?branch=master

A set of useful tools for competitive data science.

Installation

------------

To install Heamy, simply:

.. code:: bash

    $ pip install -U heamy

Features

--------

* Automatic caching (data preprocessing, predictions from models)

* Ensemble learning (stacking, blending, weighted average, etc.).

Links

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* API reference: http://heamy.readthedocs.io/en/latest/

* Examples: https://github.com/rushter/heamy/tree/master/examples

* Ensemble learning guide http://mlwave.com/kaggle-ensembling-guide/