Two-class Classification With Various Caharacteristics Based on Kernel Principal Component Analysis and Support Vector Machines  

Oleh:

Timotius, Ivanna Kristianti ; Setyawan, Iwan ; Febrianto, Andreas Ardian

Jenis: Article from Journal - ilmiah nasional - terakreditasi DIKTI
Dalam koleksi: Makara Journal of Technology vol. 15 no. 1 (Apr. 2011), page 96-100.
Topik: Characteristic; Classification; Face Recognition; Kernel Principal Component Analysis; Support Vector Machines

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: MM64.4 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

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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