Corpus ID: 235652436

Single and Union Non-parallel Support Vector Machine Frameworks

@inproceedings{Li2019SingleAU,
  title={Single and Union Non-parallel Support Vector Machine Frameworks},
  author={Chun-Na Li and Yuan-Hai Shao and Huajun Wang and Yu-Ting Zhao and Ling-Wei Huang and Naihua Xiu and Naiyang Deng},
  year={2019}
}
Considering the classification problem, we summarize the nonparallel support vector machines with the nonparallel hyperplanes to two types of frameworks. The first type constructs the hyperplanes separately. It solves a series of small optimization problems to obtain a series of hyperplanes, but is hard to measure the loss of each sample. The other type constructs all the hyperplanes simultaneously, and it solves one big optimization problem with the ascertained loss of each sample. We give the… Expand

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SHOWING 1-10 OF 107 REFERENCES
Nonparallel Support Vector Machines for Pattern Classification
TLDR
Experimental results on lots of datasets show the effectiveness of the NPSVM in both sparseness and classification accuracy, and confirm the above conclusion further. Expand
Nonparallel Hyperplanes Support Vector Machine for Multi-class Classification
TLDR
A nonparallel hyperplanes classifier for multi-class classification, termed as NHCMC, that inherits the idea of multiple birth support vector machine (MBSVM), that is the "max" decision criterion instead of the "min" one, but it has the incomparable advantages. Expand
All-in-one multicategory least squares nonparallel hyperplanes support vector machine
TLDR
Experimental results demonstrate that MLSNHSVM has significantly higher classification accuracy as compared to other multi-class classifiers and is considerably efficient than multi- class SVM in terms of computational time. Expand
Nonparallel hyperplane support vector machine for binary classification problems
TLDR
The proposed NHSVM is formulated by clustering the training points according to the similarity between classes, and is consistent between its predicting and training processes - an essential difference that distinguishes it from other nonparallel SVMs. Expand
Epsilon-nonparallel support vector regression
TLDR
This work constructs two nonparallel hyperplanes in such a way that each one is closer to one of the training patterns, and as far as possible from the other, in a novel method called epsilon-nonparallel support vector regression (ε-NPSVR). Expand
An Improved Nonparallel Support Vector Machine.
TLDR
In this article, an improved nonparallel support vector machine (INPSVM) is proposed for pattern classification and it is shown that INPSVM is superior to other algorithms in efficiency, accuracy, and robustness. Expand
Nonparallel Support Vector Ordinal Regression
TLDR
The new model constructs a hyperplane for each rank such that the patterns of this rank lie in the close proximity while maintaining clear separation with the other ranks, and design an efficient solver at the same time for training the hyperplanes in NPSVOR based on the alternating direction method of multipliers. Expand
Multiview Learning With Generalized Eigenvalue Proximal Support Vector Machines
TLDR
Multiview GEPSVMs (MvGSVMs) are proposed which effectively combine two views by introducing a multiview co-regularization term to maximize the consensus on distinct views, and skillfully transform a complicated optimization problem to a simple generalized eigenvalue problem. Expand
Weighted Twin Support Vector Machines with Local Information and its application
TLDR
A novel nonparallel plane classifier, called Weighted Twin Support Vector Machines with Local Information (WLTSVM), which mines as much underlying similarity information within samples as possible and has its additional advantages. Expand
Multisurface proximal support vector machine classification via generalized eigenvalues
TLDR
Tests on simple examples as well as on a number of public data sets show the advantages of the proposed approach in both computation time and test set correctness. Expand
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