Made available in DSpace on 2016-08-29T15:33:25Z (GMT). No. of bitstreams: 1
tese_9881_Ata de defesa.pdf: 679815 bytes, checksum: bd13283b6e7f400de68b79f04cf0b4a9 (MD5)
Previous issue date: 2016-05-20 / The objective of this work is to present the effectiveness and efficiency of algorithms for solving the loss minimization problem in Multi-Label Classification (MLC). We first prove that a specific case of loss minimization in MLC isNP-complete for the loss functions Coverage and Search Length, and therefore,no efficient algorithm for solving such problems exists unless P=NP. Furthermore, we show a novel approach for evaluating multi-label algorithms that has the advantage of not being limited to some chosen base learners, such as K-neareast Neighbor and Support Vector Machine, by simulating the distribution of labels according to multiple Beta Distributions.
| Identifer | oai:union.ndltd.org:IBICT/oai:dspace2.ufes.br:10/4309 |
| Date | 20 May 2016 |
| Creators | MELLO, L. H. S. |
| Contributors | RODRIGUES, A. L., Rauber, T. W., CARVALHO, A. P., Varejão, F. M. |
| Publisher | Universidade Federal do Espírito Santo, Mestrado em Informática, Programa de Pós-Graduação em Informática, UFES, BR |
| Source Sets | IBICT Brazilian ETDs |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis |
| Format | text |
| Source | reponame:Repositório Institucional da UFES, instname:Universidade Federal do Espírito Santo, instacron:UFES |
| Rights | info:eu-repo/semantics/openAccess |
Page generated in 0.002 seconds