Combining meta-learning and optimization algorithms for parameter selection

• Type: Article in International Conference Proceedings Book
• Date: 2012

Authors

Gomes, T (Author) Other; Miranda, P (Author) Other; Prudencio, R (Author) Other; Carlos Soares (Author) FEP; Carvalho, A (Author) Other

Conference proceedings International

Title: CEUR Workshop Proceedings

Pages: 6-7

5th Planning to Learn Workshop, PlanLearn 2012 at 2012 European Conference on Artificial Intelligence, ECAI 2012

28 August 2012

Indexing

Scopus - 1 Citation

Other information

Authenticus ID: P-00K-SPY

Abstract (EN): In this article we investigate the combination of meta-learning and optimization algorithms for parameter selection. We discuss our general proposal as well as present the recent develop-ments and experiments performed using Support Vector Machines (SVMs). Meta-learning was combined to single and multi-objective optimization techniques to select SVM parameters. The hybrid meth-ods derived from the proposal presented better results on predictive accuracy than the use of traditional optimization techniques.

Language: English

Type (Professor's evaluation): Scientific