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		<doi>10.1109/SIBGRAPI.2011.25</doi>
		<citationkey>NakamuraPerePapaFalc:2011:OpFoPr</citationkey>
		<title>Optimum-path forest pruning parameter estimation through harmony search</title>
		<format>DVD, On-line.</format>
		<year>2011</year>
		<numberoffiles>1</numberoffiles>
		<size>199 KiB</size>
		<author>Nakamura, Rodrigo Yuji Mizobe,</author>
		<author>Pereira, Clayton Reginaldo,</author>
		<author>Papa, Joao Paulo,</author>
		<author>Falcao, Alexandre Xavier,</author>
		<affiliation>UNESP - Univ Estadual Paulista</affiliation>
		<affiliation>UNESP - Univ Estadual Paulista</affiliation>
		<affiliation>UNESP - Univ Estadual Paulista</affiliation>
		<affiliation>University of Campinas</affiliation>
		<editor>Lewiner, Thomas,</editor>
		<editor>Torres, Ricardo,</editor>
		<e-mailaddress>papa.joaopalo@gmail.com</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 24 (SIBGRAPI)</conferencename>
		<conferencelocation>Maceió, AL, Brazil</conferencelocation>
		<date>28-31 Aug. 2011</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>Optimum-Path Forest, Supervised classification, Pattern Recognition.</keywords>
		<abstract>Pattern recognition in large amount of data has been paramount in the last decade, since that is not straightforward to design interactive and real time classification systems. Very recently, the Optimum-Path Forest classifier was proposed to overcome such limitations, together with its training set pruning algorithm, which requires a parameter that has been empirically set up to date. In this paper, we propose a Harmony Search-based algorithm that can find near optimal values for that. The experimental results have showed that our algorithm is able to find proper values for the OPF pruning algorithm parameter.</abstract>
		<language>en</language>
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