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Full-Text Articles in Computer Engineering
Two-Class Classification With Various Characteristics Based On Kernel Principal Component Analysis And Support Vector Machines, Ivanna Kristianti Timotius, Iwan Setyawan, Andreas Ardian Febrianto
Two-Class Classification With Various Characteristics Based On Kernel Principal Component Analysis And Support Vector Machines, Ivanna Kristianti Timotius, Iwan Setyawan, Andreas Ardian Febrianto
Makara Journal of Technology
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%.
Algorithms For Training Large-Scale Linear Programming Support Vector Regression And Classification, Pablo Rivas Perea
Algorithms For Training Large-Scale Linear Programming Support Vector Regression And Classification, Pablo Rivas Perea
Open Access Theses & Dissertations
The main contribution of this dissertation is the development of a method to train a Support Vector Regression (SVR) model for the large-scale case where the number of training samples supersedes the computational resources. The proposed scheme consists of posing the SVR problem entirely as a Linear Programming (LP) problem and on the development of a sequential optimization method based on variables decomposition, constraints decomposition, and the use of primal-dual interior point methods. Experimental results demonstrate that the proposed approach has comparable performance with other SV-based classifiers. Particularly, experiments demonstrate that as the problem size increases, the sparser the solution …