A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
The nature of statistical learning theory
The nature of statistical learning theory
Machine Learning
Applications of Support Vector Machines for Pattern Recognition: A Survey
SVM '02 Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
Support Vector Machine for Regression and Applications to Financial Forecasting
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6 - Volume 6
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Multisurface Proximal Support Vector Machine Classification via Generalized Eigenvalues
IEEE Transactions on Pattern Analysis and Machine Intelligence
Twin Support Vector Machines for Pattern Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Knowledge and Data Engineering
Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
Training support vector machines with multiple equality constraints
ECML'05 Proceedings of the 16th European conference on Machine Learning
A two-stage evolutionary algorithm based on sensitivity and accuracy for multi-class problems
Information Sciences: an International Journal
Twin Mahalanobis distance-based support vector machines for pattern recognition
Information Sciences: an International Journal
Successive overrelaxation for support vector machines
IEEE Transactions on Neural Networks
Asymptotic convergence of an SMO algorithm without any assumptions
IEEE Transactions on Neural Networks
Reduced Support Vector Machines: A Statistical Theory
IEEE Transactions on Neural Networks
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
IEEE Transactions on Neural Networks
Improvements on Twin Support Vector Machines
IEEE Transactions on Neural Networks
Robust twin support vector machine for pattern classification
Pattern Recognition
A twin-hypersphere support vector machine classifier and the fast learning algorithm
Information Sciences: an International Journal
A support vector machine-based context-ranking model for question answering
Information Sciences: an International Journal
Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions
Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions
A vector-valued support vector machine model for multiclass problem
Information Sciences: an International Journal
A proximal classifier with consistency
Knowledge-Based Systems
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In this paper, we propose a nonparallel hyperplane support vector machine (NHSVM) for binary classification problems. Our proposed NHSVM is formulated by clustering the training points according to the similarity between classes. It constructs two nonparallel hyperplanes simultaneously by solving a single quadratic programming problem, and is consistent between its predicting and training processes - an essential difference that distinguishes it from other nonparallel SVMs. This proposed NHSVM has been analyzed theoretically and implemented experimentally. The results of experiments conducted using it on both artificial and publicly available benchmark datasets confirm its feasibility and efficacy, especially for ''Cross Planes'' datasets and datasets with heteroscedastic noise.