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http://www.robots.ox.ac.uk/~minhhoai/papers/SVMFeatureWeight_PR.pdf
M.H. Nguyen, F. de la Torre / Pattern Recognition 43 (2010) 584–591 585. ARTICLE IN PRESS Let us consider the normalized margin as the ratio of the margin over the square root of sum of squared distances (in the feature ... Optimal feature selection for support vector machines
https://www.sciencedirect.com/science/article/pii/S0016003214001355
Embedded feature-selection support vector machine for driving pattern recognition ... Support vector machine with embedded feature selection. Support Vector Machines (SVM), proposed by Vapnik and his group at AT&T Bell Laboratories, are among the best off-the-shelf supervised learning algorithms. ...Cited by: 13
https://www.amazon.com/Machines-Classification-Advances-Computer-Recognition/dp/1849960976
Support Vector Machines for Pattern Classification (Advances in Computer Vision and Pattern Recognition) [Shigeo Abe] on Amazon.com. *FREE* shipping on qualifying offers. A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function …Cited by: 1566
https://www.researchgate.net/profile/Quanzhong_Liu/publication/220637867_Feature_selection_for_support_vector_machines_with_RBF_kernel/links/557ea92508aeea18b777e492.pdf
Feature selection for support vector machines kernel (SVM), a Nearest Neighbor with five neighbors (5NN), and a Nearest Neighbor with 10 neighbors (10NN) to …
https://www.researchgate.net/publication/220637867_Feature_selection_for_support_vector_machines_with_RBF_kernel
AIR'11-Feature selection for support vector machines with RBF kernel.pdf. ... F eature selection f or support vector machines. ... been an acti ve research area in pattern recognition, machine ...
https://en.wikipedia.org/wiki/Feature_selection
One other popular approach is the Recursive Feature Elimination algorithm, commonly used with Support Vector Machines to repeatedly construct a model and remove features with low weights. Embedded methods are a catch-all group of techniques which perform feature selection as part of the model construction process.
https://www.springer.com/gp/book/9781849960977
"This broad and deep … book is organized around the highly significant concept of pattern recognition by support vector machines (SVMs). … The book is praxis and application oriented but with strong theoretical backing and support.Author: Shigeo Abe
https://www.sciencedirect.com/science/article/pii/S0957417405002083
Support Vector Machines, one of the new techniques for pattern classification, have been widely used in many application areas. The kernel parameters setting for SVM in a training process impacts on the classification accuracy. Feature selection is another factor that impacts classification accuracy.Cited by: 1342
https://www.hindawi.com/journals/tswj/2013/419187/
This paper offers a hybrid approach that uses the artificial bee colony (ABC) algorithm for feature selection and support vector machines for classification. The purpose of this paper is to test the effect of elimination of the unimportant and obsolete features of the datasets on the success of the classification, using the SVM classifier. The developed approach conventionally used in liver ...Cited by: 64
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.723.5893&rep=rep1&type=pdf
Applications of Support Vector Machines for Pattern Recognition 217 Φ: Rn → H, and the linear classification problem is formulated in the new space with dimension d.The training algorithm then only depends on the data through dot prod-
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