标题： 河流：用于Python流数据的机器学习 显示英文标题

标题： River: machine learning for streaming data in Python

摘要： 河流是一个用于动态数据流和持续学习的机器学习库。 它提供了多种最先进的学习方法、数据生成器/转换器、性能指标和评估器，用于不同的流学习问题。 它是Python中两个最流行的流学习包：Creme和scikit-multiflow合并的结果。 河流基于从开创性包中获得的经验，引入了一个重新设计的架构。 河流的抱负是成为处理流数据机器学习的首选库。 此外，这个开源包将大量从业者和研究人员社区汇集在同一个平台上。 源代码可在https://github.com/online-ml/river获取。 显示英文摘要

摘要： River is a machine learning library for dynamic data streams and continual learning. It provides multiple state-of-the-art learning methods, data generators/transformers, performance metrics and evaluators for different stream learning problems. It is the result from the merger of the two most popular packages for stream learning in Python: Creme and scikit-multiflow. River introduces a revamped architecture based on the lessons learnt from the seminal packages. River's ambition is to be the go-to library for doing machine learning on streaming data. Additionally, this open source package brings under the same umbrella a large community of practitioners and researchers. The source code is available at https://github.com/online-ml/river.