Proximal support vector machine classifiers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graph Embedding: A General Framework for Dimensionality Reduction
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Multisurface Proximal Support Vector Machine Classification via Generalized Eigenvalues
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data Fusion and Multicue Data Matching by Diffusion Maps
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy multi-category proximal support vector classification via generalized eigenvalues
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Regularized locality preserving indexing via spectral regression
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
A classification method based on generalized eigenvalue problems
Optimization Methods & Software - Systems Analysis, Optimization and Data Mining in Biomedicine
Discriminatively regularized least-squares classification
Pattern Recognition
Nonparallel plane proximal classifier
Signal Processing
Journal of Field Robotics - Special Issue on LAGR Program, Part II
Least squares twin support vector machines for pattern classification
Expert Systems with Applications: An International Journal
Locality sensitive discriminant analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Proximal support vector machine using local information
Neurocomputing
Multi-weight vector projection support vector machines
Pattern Recognition Letters
Localized twin SVM via convex minimization
Neurocomputing
Fuzzy proximal support vector classification via generalized eigenvalues
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
Nearest neighbor pattern classification
IEEE Transactions on Information Theory
Twin least squares support vector regression
Neurocomputing
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A Twin Support Vector Machine (TWSVM), as a variant of a Multisurface Proximal Support Vector Machine via Generalized Eigenvalues (GEPSVM), attempts to improve the generalization of GEPSVM, whose solution follows from solving two quadratic programming problems (QPPs), each of which is smaller than in a standard SVM. Unfortunately, the two QPPs still lead to rather high computational costs. Moreover, although TWSVM has better classification performance than GEPSVM, a major disadvantage is it fails to exploit the underlying correlation or similarity information between any pair of data points with the same labels that may be important for classification performance as much as possible. To mitigate the above deficiencies, in this paper, we propose a novel nonparallel plane classifier, called Weighted Twin Support Vector Machines with Local Information (WLTSVM). WLTSVM mines as much underlying similarity information within samples as possible. This method not only retains the superior characteristics of TWSVM, but also has its additional advantages: (1) comparable or better classification accuracy compared to SVM, GEPSVM and TWSVM; (2) taking motivation from standard SVM, the concept of support vectors is retained; (3) more efficient than TWSVM in terms of computational costs; and (4) only one penalty parameter is considered as opposed to two in TWSVM. Finally, experiments on both simulated and real problems confirm the effectiveness of our method.