Please use this identifier to cite or link to this item: http://hdl.handle.net/10216/65852
Author(s): Adriana S. Iwashita
João P. Papa
Alexandre X. Falcão
Roberto A. Lotufo
Victor M. de Araújo
Victor H. Costa de Albuquerque
João Manuel R. S. Tavares
Title: Speeding up optimum-path forest training by path-cost propagation
Issue Date: 2012
Abstract: In this paper we present an optimization of the Optimum-Path Forest classifier training procedure, which is based on a theoretical relationship between minimum spanning forest and optimum-path forest for a specific path-cost function. Experiments on public datasets have shown that the proposed approach can obtain similar accuracy to the traditional one hut with faster data training.
Subject: Ciências Tecnológicas, Ciências da engenharia e tecnologias
Call Number: 68554
URI: http://hdl.handle.net/10216/65852
Source: 2012 21ST INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR 2012)
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: openAccess
License: https://creativecommons.org/licenses/by-nc/4.0/
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

Files in This Item:
File Description SizeFormat 
68554.pdfPaper67.22 kBAdobe PDFThumbnail
View/Open


This item is licensed under a Creative Commons License Creative Commons