Scikit-Multiflow:一个多输出流框架

Jacob Montiel, J. Read, A. Bifet, T. Abdessalem
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引用次数: 235

摘要

Scikit-multiflow是Python编程语言的多输出/多标签和流数据挖掘框架。作为一个鼓励流学习研究民主化的平台,它为流学习、流生成器和评估器提供了多种最先进的方法。scikit-multiflow建立在流行的开源框架之上,包括scikit-learn、MOA和MEKA。开发遵循自由/开源软件原则,并通过遵守PEP8指导方针和使用持续集成和自动测试来强制执行质量。源代码可以在这个https URL上公开获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scikit-Multiflow: A Multi-output Streaming Framework
Scikit-multiflow is a multi-output/multi-label and stream data mining framework for the Python programming language. Conceived to serve as a platform to encourage democratization of stream learning research, it provides multiple state of the art methods for stream learning, stream generators and evaluators. scikit-multiflow builds upon popular open source frameworks including scikit-learn, MOA and MEKA. Development follows the FOSS principles and quality is enforced by complying with PEP8 guidelines and using continuous integration and automatic testing. The source code is publicly available at this https URL.
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