Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
The nature of statistical learning theory
The nature of statistical learning theory
Pairwise classification and support vector machines
Advances in kernel methods
Support vector machine pairwise classifiers with error reduction for image classification
MULTIMEDIA '01 Proceedings of the 2001 ACM workshops on Multimedia: multimedia information retrieval
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Improved Pairwise Coupling Classification with Correcting Classifiers
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifiers
Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifiers
Reducing multiclass to binary: a unifying approach for margin classifiers
The Journal of Machine Learning Research
Solving multiclass learning problems via error-correcting output codes
Journal of Artificial Intelligence Research
The evidence framework applied to support vector machines
IEEE Transactions on Neural Networks
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
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In this paper, a novel structure is proposed to extend standard support vector classifier to multi-class cases. For a K-class classification task, an array of K optimal pairwise coupling classifier (O-PWC) is constructed, each of which is the most reliable and optimal for the corresponding class in the sense of cross entropy or square error. The final decision will be produced through combining the results of these K O-PWCs. The accuracy rate is improved while the computational cost will not increase too much. Our approach is applied to two applications: handwritten digital recognition on MNIST database and face recognition on Cambridge ORL face database, experimental results reveal that our method is effective and efficient.