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Authors: João Freitas 1 ; Nuno Lavado 1 and Jorge Bernardino 2

Affiliations: 1 Coimbra Polytechnic – ISEC, Rua Pedro Nunes, 3030-199 Coimbra and Portugal ; 2 Coimbra Polytechnic – ISEC, Rua Pedro Nunes, 3030-199 Coimbra, Portugal, CISUC - Centre of Informatics and Systems of University of Coimbra, DEI, Polo 2, 3030-290 Coimbra and Portugal

Keyword(s): Data Science, Machine Learning, AutoML, Auto-WEKA, OpenML, Benchmarking.

Related Ontology Subjects/Areas/Topics: Business Analytics ; Data Engineering ; Predictive Modeling

Abstract: Machine Learning model building is an important and complex task in Data Science but also a good target for automation as recently exploited by AutoML. In general, free and open-source packages offer a joint space of learning algorithms and their respective hyperparameter settings and an optimization method for model search and tuning. In this paper, Auto-WEKA’s performance has been tested by running it for short periods of time (5, 15 and 30 minutes) using a commodity machine and suitable datasets with a limited number of observations and features. Benchmarking was performed against the best human-generated solution available in OpenML for each selected dataset. We concluded that increasing the overall time budget available over the previous values didn’t improve significantly classifiers’ performance.

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Paper citation in several formats:
Freitas, J.; Lavado, N. and Bernardino, J. (2018). Benchmarking Auto-WEKA on a Commodity Machine. In Proceedings of the 7th International Conference on Data Science, Technology and Applications - DATA; ISBN 978-989-758-318-6; ISSN 2184-285X, SciTePress, pages 180-186. DOI: 10.5220/0006914801800186

@conference{data18,
author={João Freitas. and Nuno Lavado. and Jorge Bernardino.},
title={Benchmarking Auto-WEKA on a Commodity Machine},
booktitle={Proceedings of the 7th International Conference on Data Science, Technology and Applications - DATA},
year={2018},
pages={180-186},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006914801800186},
isbn={978-989-758-318-6},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Data Science, Technology and Applications - DATA
TI - Benchmarking Auto-WEKA on a Commodity Machine
SN - 978-989-758-318-6
IS - 2184-285X
AU - Freitas, J.
AU - Lavado, N.
AU - Bernardino, J.
PY - 2018
SP - 180
EP - 186
DO - 10.5220/0006914801800186
PB - SciTePress