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Comparing different performance estimation methods for time series forecasting tasks

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Time Series Forecasting Performance Estimation

This repository contains the code and datasets used for experiments conducted in the following paper:

Cerqueira, V., Torgo, L., & Mozetič, I. (2020). Evaluating time series forecasting models: An empirical study on performance estimation methods. Machine Learning, 109(11), 1997-2028.

Citation

If you use this code or the findings in your research, please cite:

@article{cerqueira2020evaluating,
  title={Evaluating time series forecasting models: An empirical study on performance estimation methods},
  author={Cerqueira, Vitor and Torgo, Luis and Mozeti{\v{c}}, Igor},
  journal={Machine Learning},
  volume={109},
  number={11},
  pages={1997--2028},
  year={2020},
  publisher={Springer}
}

Running

The main script is perfestimation-rw.r.

The script perfestimation-synthetic.r is only ran for a specific (dataset, algorithm) pair. You need to change those to get the results for a different pair.

Contact

Get in touch at [email protected]

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Comparing different performance estimation methods for time series forecasting tasks

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