Speeding up optimum-path forest training by path-cost propagation

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

Authors

Adriana S. Iwashita (Author) Other; João P. Papa (Author) Other; Alexandre X. Falcão (Author) Other; Roberto A. Lotufo (Author) Other; Victor M. de Araújo (Author) Other; Victor H. Costa de Albuquerque (Author) FEUP; João Manuel R. S. Tavares (Author) FEUP

Conference proceedings International

Title: 2012 21ST INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR 2012)

Pages: 1233-1236

21st International Conference on Pattern Recognition (ICPR)

Tsukuba, JAPAN, NOV 11-15, 2012

Indexing

ISI Web of Knowledge - 3 Citations

ISI Web of Science

Scopus - 2 Citations

INSPEC

Scientific classification

FOS: Engineering and technology

CORDIS: Technological sciences

Other information

Authenticus ID: P-008-9PY

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4