TWO-CLASS CLASSIFICATION WITH VARIOUS CHARACTERISTICS BASED ON KERNEL PRINCIPAL COMPONENT ANALYSIS AND SUPPORT VECTOR MACHINES
| Main Authors: | Ivanna Kristianti Timotius; Department of Electronic Engineering, Satya Wacana Christian University, Salatiga 50711, Indonesia, 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 |
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| Format: | Article application/ eJournal |
| Bahasa: | eng |
| Terbitan: |
Directorate of Research and Community Engagement, Universitas Indonesia
, 2011
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| Online Access: |
http://journal.ui.ac.id/index.php/technology/article/view/863 |
Daftar Isi:
- 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%. Keywords: characteristic, classification, face recognition, kernel principal component analysis, support vector machines