The nature of statistical learning theory
The nature of statistical learning theory
Fuzzy least squares support vector machines for multiclass problems
Neural Networks - 2003 Special issue: Advances in neural networks research — IJCNN'03
Bounds on Error Expectation for Support Vector Machines
Neural Computation
A review on the combination of binary classifiers in multiclass problems
Artificial Intelligence Review
Adapting decision DAGs for multipartite ranking
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Enhancing directed binary trees for multi-class classification
Information Sciences: an International Journal
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This paper proposes a method to improve generalization performance of multi-class support vector machines (SVM) based on directed acyclic graph (DAG). At first the structure of DAG is optimized according to training data and Jaakkola-Haussler bound, and then we define fuzzy membership function for each class which is obtained by using average operator in the testing stage and the final recognition result is the class with maximum membership. As a result of our experiment for similar handwritten Chinese characters recognition, the generalization ability of the novel fuzzy multi-class DAG-based SVM classifier is better than that of pair-wise SVM classifier with other combination strategies and its execution time is almost the same as the original DAG.