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https://www.researchgate.net/publication/221532218_Localized_Support_Vector_Machines_for_Classification
Support vector machines (SVMs) have been promising methods in pattern recognition because of their solid mathematical foundation. In this paper, we propose a localized SVM classification scheme ...
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/two-class-locally-deep-support-vector-machine
Module overview. This article describes how to use the Two-Class Locally Deep Support Vector Machine module in Azure Machine Learning Studio (classic), to create a two-class, non-linear support vector machines (SVM) classifier that is optimized for efficient prediction.. Support vector machines (SVMs) are an extremely popular and well-researched class of supervised learning models, which can ...
https://arxiv.org/pdf/1903.01334
Quantitative Robustness of Localized Support Vector Machines Florian Dumpert Department of Mathematics, University of Bayreuth, Germany Abstract The huge amount of available data nowadays is a challenge for kernel-based machine learning algorithms like SVMs with respect to runtime and storage capacities. Local approaches mightAuthor: Florian Dumpert
http://www.cse.msu.edu/~ptan/papers/tkde-lsvm.pdf
Efficient Algorithm for Localized Support Vector Machine Haibin Cheng, Pang-Ning Tan,Member, IEEE, and Rong Jin, Member, IEEE Abstract—This paper presents a framework called Localized Support Vector Machine (LSVM) for classifying data with nonlinear decision surfaces.
https://arxiv.org/abs/1903.01334
The huge amount of available data nowadays is a challenge for kernel-based machine learning algorithms like SVMs with respect to runtime and storage capacities. Local approaches might help to relieve these issues and to improve statistical accuracy. It has already been shown that these local approaches are consistent and robust in a basic sense. This article refines the analysis of robustness ...Author: Florian Dumpert
https://www.sciencedirect.com/science/article/pii/S0925231218307999
As pointed out in there is a need to have a closer look at localized approaches of machine learning algorithms like support vector machines and related methods. With regard to big data the massive amount of available data potentially used to discover patters is a challenge for algorithms with respect to runtime and storage capacities.Cited by: 4
https://www.hindawi.com/journals/sv/2015/469165/
To improve the adaptability of volatile time series, several modified SVR machines, such as localized support vector regression (LSVR) and piecewise support vector regression , have been developed and applied in the field of financial analysis. In this paper, a novel SVR machine, called adaptive support vector regression (ASVR), is proposed to ...Cited by: 2
http://web.mit.edu/6.034/wwwbob/svm.pdf
•Support vector machines Support Vectors again for linearly separable case •Support vectors are the elements of the training set that would change the position of the dividing hyperplane if removed. •Support vectors are the critical elements of the training set …
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