A comparative analysis of attribute reduction algorithms applied to wet-blue leather defects classification.

A comparative analysis of attribute reduction algorithms applied to wet-blue leather defects classification.

This paper presents an attribute reduction comparative study on four linear discriminant analysis techniques: FisherFace, CLDA, DLDA and YLDA. The attribute reduction has been applied to the problem of leather defect c1assification using four different c1assifiers: C4.5, KNN, Naive Bayes and Support Veetor Machines. Results and analyses on the performance of correct c1assification rates as the number of attributes were reduced are reported.

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Bibliographic Details
Main Authors: AMORIM, W. P., PISTORI, H., JACINTO, M. A. C.
Other Authors: WILLIAN PARAGUASSI AMORIM, UFMS/CAMPO GRANDE, MS; HEMERSON PISTORI, UCDB/CAMPO GRANDE, MS; MANUEL ANTONIO CHAGAS JACINTO, CPPSE.
Format: Separatas biblioteca
Language:pt_BR
por
Published: 2009-11-13
Subjects:Wet-blue, Defeito., Couro.,
Online Access:http://www.alice.cnptia.embrapa.br/alice/handle/doc/574710
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http://www.alice.cnptia.embrapa.br/alice/handle/doc/574710

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