ml_edm package: a Python toolkit for Machine Learning based Early Decision Making
This is an incremental software package for researchers working on early classification of time series.
The authors introduced ml_edm, a Python toolkit for early decision making in machine learning tasks with temporal data, providing modular implementations of state-of-the-art algorithms and compatibility with scikit-learn.
\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}.