Results 291 to 300 of about 350,996 (311)
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IEEE Transactions on Neural Networks, 2002
A support vector machine (SVM) learns the decision surface from two distinct classes of the input points. In many applications, each input point may not be fully assigned to one of these two classes. In this paper, we apply a fuzzy membership to each input point and reformulate the SVMs such that different input points can make different contributions ...
Lin, Chun-Fu, Wang, Sheng-De
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A support vector machine (SVM) learns the decision surface from two distinct classes of the input points. In many applications, each input point may not be fully assigned to one of these two classes. In this paper, we apply a fuzzy membership to each input point and reformulate the SVMs such that different input points can make different contributions ...
Lin, Chun-Fu, Wang, Sheng-De
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ACM SIGKDD Explorations Newsletter, 2000
Support Vector Machines (SVMs) and related kernel methods have become increasingly popular tools for data mining tasks such as classification, regression, and novelty detection. The goal of this tutorial is to provide an intuitive explanation of SVMs from a geometric perspective.
Kristin P. Bennett, Colin Campbell
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Support Vector Machines (SVMs) and related kernel methods have become increasingly popular tools for data mining tasks such as classification, regression, and novelty detection. The goal of this tutorial is to provide an intuitive explanation of SVMs from a geometric perspective.
Kristin P. Bennett, Colin Campbell
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American Journal of Orthodontics and Dentofacial Orthopedics, 2023
Dirk Valkenborg +3 more
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Dirk Valkenborg +3 more
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Structural Support Vector Machine
2008Support Vector Machine (SVM) is one of the most popular classifiers in pattern recognition, which aims to find a hyperplane that can separate two classes of samples with the maximal margin. As a result, traditional SVM usually more focuses on the scatter between classes, but neglects the different data distributions within classes which are also vital ...
Hui Xue 0002 +2 more
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On Consistency and Stability of Support Vector Machines and Localized Support Vector Machines
In recent years, the demand for machine learning and artificial intelligence has grown rapidly. This has manifested itself in a drastic increase in the number of existing applications as well as in the pervasiveness of these applications. In these, different machine learning methods have shown enormous empirical success in accurately capturing ...openaire +2 more sources
Lagrangian support vector machines
J. Mach. Learn. Res., 2001Summary: An implicit Lagrangian for the dual of a simple reformulation of the standard quadratic program of a linear support vector machine is proposed. This leads to the minimization of an unconstrained differentiable convex function in a space of dimensionality equal to the number of classified points.
Olvi L. Mangasarian, David R. Musicant
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An improved multiple birth support vector machine for pattern classification
Neurocomputing, 2017Shifei Ding, Yu Xue
exaly
TSVR: An efficient Twin Support Vector Machine for regression
Neural Networks, 2010Xinjun Peng
exaly
Research on the hybrid models of granular computing and support vector machine
Artificial Intelligence Review, 2013Shifei Ding +2 more
exaly
Credit scoring using the clustered support vector machine
Expert Systems With Applications, 2015Terry Harris
exaly