Abstract
Meta-learning can be seen as alternating the construction of configuration of learning machines for validation, scheduling of such tasks and the meta-knowledge collection. This article presents a few modifications of complexity measures and their application in advising to scheduling test tasks - validation tasks of learning machines in meta-learning process. Additionally some comments about their optimality in context of meta-learning are presented. © 2013 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Jankowski, N. (2013). Complexity measures for meta-learning and their optimality. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7070 LNAI, pp. 198–210). Springer Verlag. https://doi.org/10.1007/978-3-642-44958-1_15
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