ActivMetaL: Algorithm Recommendation with Active Meta Learning
| Autor: | Sun-Hosoya, Lisheng, Guyon, Isabelle, Sebag, Michèle |
|---|---|
| Přispěvatelé: | TAckling the Underspecified (TAU), Laboratoire de Recherche en Informatique (LRI), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Sun-Hosoya, Lisheng |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] [INFO]Computer Science [cs] [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG] [INFO] Computer Science [cs] [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] |
| Zdroj: | IAL 2018 workshop, ECML PKDD IAL 2018 workshop, ECML PKDD, Sep 2018, Dublin, Ireland. 2018 IAL 2018 workshop, ECML PKDD, Sep 2018, Dublin, Ireland., 2018 |
| Popis: | International audience; We present an active meta learning approach to model selection or algorithm recommendation. We adopt the point of view "collab-orative filtering" recommender systems in which the problem is brought back to a missing data problem: given a sparsely populated matrix of performances of algorithms on given tasks, predict missing performances; more particularly, predict which algorithm will perform best on a new dataset (empty row). In this work, we propose and study an active learning version of the recommender algorithm CofiRank algorithm and compare it with baseline methods. Our benchmark involves three real-world datasets (from StatLog, OpenML, and AutoML) and artificial data. Our results indicate that CofiRank rapidly finds well performing algorithms on new datasets at reasonable computational cost. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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