Published September 7, 2021 | Version v2021.09.07
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HMProenca/robust-rules-for-prediction-and-description

Authors/Creators

  • 1. LIACS

Description

Robust rules for prediction and description

This repository contains the code for the experiments of the PhD dissertation Robust rules for prediction and description at the time of publication.

The content of these folders is the following:

Licenses

Please refer to each folder and algorithm for their specific licenses.

References in which this work is based upon

Files

HMProenca/robust-rules-for-prediction-and-description-v2021.09.07.zip

Files (108.2 MB)

Additional details

References

  • Proença, Hugo M., and Matthijs van Leeuwen. "Interpretable multiclass classification by MDL-based rule lists." Information Sciences 512 (2020): 1372-1393.
  • Proença, Hugo M., Peter D. Grünwald, et al. (2020). "Discovering outstanding subgroup lists for numeric targets using MDL". In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML/PKDD'20
  • Proença, Hugo M., Thomas Bäck, and Matthijs van Leeuwen. "Robust subgroup discovery." arXiv preprint arXiv:2103.13686 (2021).
  • Proença, Hugo M., et al. "Identifying flight delay patterns using diverse subgroup discovery." 2018 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2018.