xcsf

Name	xcsf JSON
Version	1.4.7 JSON
	download
home_page	https://github.com/xcsf-dev/xcsf
Summary	XCSF learning classifier system: rule-based evolutionary machine learning
upload_time	2024-08-19 18:38:12
maintainer	Richard Preen
docs_url	None
author	None
requires_python	>=3.9
license	GPL-3.0
keywords	divide and conquer evolutionary algorithm genetic programming learning classifier system least squares machine learning neural networks neuroevolution reinforcement learning rule-based supervised learning stochastic gradient descent xcs xcsf
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # XCSF learning classifier system

[![License](https://img.shields.io/badge/License-GPL%20v3-blue.svg?style=flat)](http://www.gnu.org/licenses/gpl-3.0)
[![Linux Build](https://img.shields.io/github/actions/workflow/status/xcsf-dev/xcsf/ubuntu_build.yml?branch=master&logo=linux&logoColor=white&style=flat&label=Ubuntu)](https://github.com/xcsf-dev/xcsf/actions?query=workflow%3A%22Ubuntu+build%22)
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[![Windows Build](https://img.shields.io/github/actions/workflow/status/xcsf-dev/xcsf/windows_build.yml?branch=master&logo=windows&logoColor=white&style=flat&label=Windows)](https://github.com/xcsf-dev/xcsf/actions?query=workflow%3A%22Windows+build%22)
[![Latest Version](https://img.shields.io/github/v/release/xcsf-dev/xcsf?style=flat)](https://github.com/xcsf-dev/xcsf/releases)
[![DOI](https://zenodo.org/badge/28035841.svg)](https://zenodo.org/badge/latestdoi/28035841)
[![Codacy](https://app.codacy.com/project/badge/Grade/986386c6706c4bcd833445150b053b06)](https://app.codacy.com/gh/xcsf-dev/xcsf/dashboard)
[![CodeFactor](https://img.shields.io/codefactor/grade/github/xcsf-dev/xcsf?logo=codefactor&style=flat)](https://www.codefactor.io/repository/github/xcsf-dev/xcsf)
[![SonarCloud](https://sonarcloud.io/api/project_badges/measure?project=xcsf-dev_xcsf&metric=alert_status)](https://sonarcloud.io/dashboard?id=xcsf-dev_xcsf)
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[![Lines of Code](https://sonarcloud.io/api/project_badges/measure?project=xcsf-dev_xcsf&metric=ncloc)](https://sonarcloud.io/dashboard?id=xcsf-dev_xcsf)
[![PyPI package](https://img.shields.io/pypi/v/xcsf.svg)](https://pypi.org/project/xcsf)
[![Python versions](https://img.shields.io/pypi/pyversions/xcsf.svg)](https://pypi.org/project/xcsf)
[![Downloads](https://static.pepy.tech/personalized-badge/xcsf?period=month&units=international_system&left_color=black&right_color=orange&left_text=PyPI%20downloads%20per%20month)](https://pepy.tech/project/xcsf)

An implementation of the XCSF [learning classifier system](https://en.wikipedia.org/wiki/Learning_classifier_system) that can be built as a stand-alone binary or as a Python library. XCSF is an accuracy-based [online](https://en.wikipedia.org/wiki/Online_machine_learning) [evolutionary](https://en.wikipedia.org/wiki/Evolutionary_computation) [machine learning](https://en.wikipedia.org/wiki/Machine_learning) system with locally approximating functions that compute classifier payoff prediction directly from the input state. It can be seen as a generalisation of XCS where the prediction is a scalar value. XCSF attempts to find solutions that are accurate and maximally general over the global input space, similar to most machine learning techniques. However, it maintains the additional power to adaptively subdivide the input space into simpler local approximations.

See the project [wiki](https://github.com/xcsf-dev/xcsf/wiki) for details on features, how to build, run, and use as a Python library.

            

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