Speeding up algorithm selection using average ranking and active testing by introducing runtime

Algorithm selection methods can be speeded-up substantially by incorporating multi-objective measures that give preference to algorithms that are both promising and fast to evaluate. In this paper, we introduce such a measure, A3R, and incorporate it into two algorithm selection techniques: average...

Full description

Saved in:

Bibliographic Details
Published in:	Machine learning Vol. 107; no. 1; pp. 79 - 108
Main Authors:	Abdulrahman, Salisu Mamman, Brazdil, Pavel, van Rijn, Jan N., Vanschoren, Joaquin
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.01.2018 Springer Nature B.V
Subjects:	Accuracy Algorithms Artificial Intelligence Computer Science Control Machine learning Mechatronics Natural Language Processing (NLP) Ranking Robotics Run time (computers) Simulation and Modeling Special Issue on Metalearning and Algorithm Selection Meta-learning Average ranking Algorithm selection Active testing Mean interval loss Ranking of algorithms Loss curves
ISSN:	0885-6125, 1573-0565
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!