ml_edm 是一个 Python 3 库，专为涉及时间/序列数据的任何学习任务的早期决策制定而设计。该包也是模块化的，为研究人员提供了一种简便的方法来实现他们自己的触发策略，用于分类、回归或任何机器学习任务。目前，许多 Early Classification of Time Series (ECTS) 最先进的算法都利用并行计算在库中高效实现。其语法遵循 scikit-learn 中引入的语法，使得估计器和管道与 ml_edm 兼容。该软件在 BSD-3-Clause 许可证下分发，源代码可在 https://github.com/ML-EDM/ml_edm 找到。
英文摘要：
\texttt{ml\_edm} is a Python 3 library, designed for early decision making of any learning tasks involving temporal/sequential data. The package is also modular, providing researchers an easy way to implement their own triggering strategy for classification, regression or any machine learning task. As of now, many Early Classification of Time Series (ECTS) state-of-the-art algorithms, are efficiently implemented in the library leveraging parallel computation. The syntax follows the one introduce in \texttt{scikit-learn}, making estimators and pipelines compatible with \texttt{ml\_edm}. This software is distributed over the BSD-3-Clause license, source code can be found at \url{https://github.com/ML-EDM/ml_edm}.
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