Skip to content

A repository with some simple implementation of Meta Heuristics (ie: ga, pso) , using sklearn and other common libraries

License

Notifications You must be signed in to change notification settings

gonzalesMK/MetaHeuristic

Repository files navigation

Coverage Pypi

MetaHeuristic

A repository with Meta Heuristics (ie: ga, pso) implementations for feature selection.

Important Links

HTML Documentation - http://metaheuristic.readthedocs.io/en/latest/

Installation and Usage

The package by itself comes with a single module and an estimator. Before installing the module you will need - Numpy - Scipy - DEAP - Matplotli - Scikit-learn

To install the module execute, python

python setup.py install

or:

pip install metaheuristic

If the installation is successful, and MetaHeuristic is correctly installed, you should be able to execute the following in Python:

>>> from feature_selection import HarmonicSearch
>>> estimator = HarmonicSearch()

DEAP

DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data structures transparent. It works in perfect harmony with parallelisation mechanism such as multiprocessing and [SCOOP](http://pyscoop.org).

See the [DEAP User's Guide](http://deap.readthedocs.org/) for DEAP documentation.

About

A repository with some simple implementation of Meta Heuristics (ie: ga, pso) , using sklearn and other common libraries

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published