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https://github.com/faiber09/ml_edm_multi

Modification of ML_EDM so that it works with multivariate time series.
https://github.com/faiber09/ml_edm_multi

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Modification of ML_EDM so that it works with multivariate time series.

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# ``ml_edm`` : A python package for Early Decision Making-based Machine Learning

Many situations require decisions to be made quickly to avoid the costs associated with delaying the decision. A doctor who needs to choose which test to perform on their patient and an agent considering whether a certain behavior on a network is caused by a hacker are examples of individuals confronted with such situations. However, taking a decision too hastily may lead to more mistakes, resulting in additional costs that could have been avoided. In these situations, where there is a trade-off between the *earliness* of the decision and the *accuracy* of the prediction, the **Machine Learning for Early Decision Making** (ML-EDM) framework offers ML solutions not only to make a prediction but also to decide when to trigger its associated decision timely.

The ``ml_edm`` package provides tools to facilitate dealing with the **Early Classification of Time Series** (ECTS) problem, whose goal is to determine the class associated with a time series before all measurements are available.

## Install

```console
# Original library:
pip install git+https://github.com/ML-EDM/ml_edm
# This Fork:
pip install git+https://github.com/Faiber09/ML_EDM_Multi
```
## What’s New in This Fork

- **Multivariate Time Series Support**
This version extends the original `ml_edm` package to handle **multivariate** time series. The upstream toolkit only supported univariate data.

- **AEON 1.0.0 Compatibility**
We’ve applied minor adjustments so that `ml_edm` now works seamlessly with **AEON ≥ 1.0.0** (the original release targeted AEON 0.4.0).

## Citation

If you use the original package, please refer to it using the following the bibtex entry:

@misc{renault2024mledmpackagepythontoolkit,
title={ml_edm package: a Python toolkit for Machine Learning based Early Decision Making},
author={Aurélien Renault and Youssef Achenchabe and Édouard Bertrand and Alexis Bondu and Antoine Cornuéjols and Vincent Lemaire and Asma Dachraoui},
year={2024},
eprint={2408.12925},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/2408.12925},
}