Given a collection of algorithms, the Algorithm Selection (AS) problem consists in identifying which of them is the best one for solving a given problem. The selection depends on a set of numerical features that characterize the problem to solve. In this paper we show the impact of feature selection techniques on the performance of the SUNNY algorithm selector, taking as reference the benchmarks of the AS library (ASlib). Results indicate that a handful of features is enough to reach similar, if not better, performance of the original SUNNY approach that uses all the available features. We also present sunny-as: a tool for using SUNNY on a generic ASlib scenario.

Feature selection for SUNNY: A study on the algorithm selection library / Amadini, Roberto; Biselli, Fabio; Gabbrielli, Maurizio; Liu, Tong; Mauro, Jacopo. - STAMPA. - (2015), pp. 7372114.25-7372114.32. (Intervento presentato al convegno 27th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2015 tenutosi a Vietri sul Mare, ITALY nel NOV 09-11, 2015) [10.1109/ICTAI.2015.18].

Feature selection for SUNNY: A study on the algorithm selection library

Amadini, Roberto;GABBRIELLI, MAURIZIO;LIU, TONG;
2015

Abstract

Given a collection of algorithms, the Algorithm Selection (AS) problem consists in identifying which of them is the best one for solving a given problem. The selection depends on a set of numerical features that characterize the problem to solve. In this paper we show the impact of feature selection techniques on the performance of the SUNNY algorithm selector, taking as reference the benchmarks of the AS library (ASlib). Results indicate that a handful of features is enough to reach similar, if not better, performance of the original SUNNY approach that uses all the available features. We also present sunny-as: a tool for using SUNNY on a generic ASlib scenario.
2015
Proceedings - 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI)
25
32
Feature selection for SUNNY: A study on the algorithm selection library / Amadini, Roberto; Biselli, Fabio; Gabbrielli, Maurizio; Liu, Tong; Mauro, Jacopo. - STAMPA. - (2015), pp. 7372114.25-7372114.32. (Intervento presentato al convegno 27th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2015 tenutosi a Vietri sul Mare, ITALY nel NOV 09-11, 2015) [10.1109/ICTAI.2015.18].
Amadini, Roberto; Biselli, Fabio; Gabbrielli, Maurizio; Liu, Tong; Mauro, Jacopo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/571037
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