Two-Class Classification with Various Characteristics Based on Kernel Principal Component Analysis and Support Vector Machines

Authors

Ivanna Kristianti Timotius, Department of Electronic Engineering, Satya Wacana Christian University, Salatiga 50711, IndonesiaFollow
Iwan Setyawan, Department of Electronic Engineering, Satya Wacana Christian University, Salatiga 50711, Indonesia
Andreas Ardian Febrianto, Department of Electronic Engineering, Satya Wacana Christian University, Salatiga 50711, Indonesia

Abstract

Two class pattern classification problems appeared in many applications. In some applications, the characteristic of the members in a class is dissimilar. This paper proposed a classification system for this problem. The proposed system was developed based on the combination of kernel principal component analysis (KPCA) and support vector machines (SVMs). This system has been implemented in a two class face recognition problem. The average of the classification rate in this face image classification is 82.5%.

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Recommended Citation

Timotius, Ivanna Kristianti; Setyawan, Iwan; and Febrianto, Andreas Ardian (2011) "Two-Class Classification with Various Characteristics Based on Kernel Principal Component Analysis and Support Vector Machines," Makara Journal of Technology: Vol. 15: Iss. 1, Article 15.
DOI: 10.7454/mst.v15i1.863
Available at: https://scholarhub.ui.ac.id/mjt/vol15/iss1/15