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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: 1 day 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 (about 2 years ago)
- Last Synced: 2024-12-15T15:07:53.269Z (8 days ago)
- Topics: data-science, machine-learning, stacking
- Language: Python
- Homepage: http://heamy.readthedocs.io/en/latest/
- Size: 89.8 KB
- Stars: 552
- Watchers: 16
- Forks: 114
- Open Issues: 8
-
Metadata Files:
- Readme: README.rst
- Contributing: CONTRIBUTING.rst
- License: LICENSE
Awesome Lists containing this project
README
=====
heamy
=====.. 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=masterA 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
-----* 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/