Code, Data, and Experimental Results for "Boosting Revisited: Benchmarking and Advancing LP-Based Ensemble Methods"

DOI:10.4121/f82dcdaa-fc94-43c5-b66d-02579bd3de4f.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/f82dcdaa-fc94-43c5-b66d-02579bd3de4f

Datacite citation style

Akkerman, Fabian; Ferry, Julien; Artigues, Christian; Hebrard, Emmanuel; Vidal, Thibaut (2025): Code, Data, and Experimental Results for "Boosting Revisited: Benchmarking and Advancing LP-Based Ensemble Methods". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/f82dcdaa-fc94-43c5-b66d-02579bd3de4f.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

This dataset contains (1) all code needed to reproduce our results, (2) the 20 data sets on which we report results, and (3) all experiment results, related to the paper: "Boosting Revisited: Benchmarking and Advancing LP-Based Ensemble Methods" as published in TMLR, see: https://openreview.net/forum?id=lscC4PZUE4.


The code is written in Python 3.12, a README inside the zipped code folder provides more details on setting up and running the code.


In the zipped data sets folder, we provide a README with more information on our preprocessing steps and links to the orginal sources from which we retrieved the data sets.


Each experiment is outputted to a JSON file. We include both the results as reported in the paper (the best-found hyperparameter setting) and all experiments related to other hyperparameter settings. The JSON files are organized in zipped folders per experiment type. See the README for further details.

History

  • 2025-10-22 first online, published, posted

Publisher

4TU.ResearchData

Format

JSON; Python; CSV

Organizations

University of Twente, Industrial Engineering and Management Science;
Polytechnique Montréal, CIRRELT & SCALE-AI Chair in Data-Driven Supply Chains;
Université de Toulouse, LAAS-CNRS

DATA

Files (4)