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https://www.kdnuggets.com/2017/08/machine-learning-abstracts-support-vector-machines.html
By Narendra Nath Joshi, Carnegie Mellon. This vector, that vector, every vector. Last post, we discussed a type of classification algorithm, Decision Trees.. There is another machine learning algorithm which can be used for classification, Support Vector Machines (SVM).
https://ieeexplore.ieee.org/document/708428
Abstract: My first exposure to Support Vector Machines came this spring when heard Sue Dumais present impressive results on text categorization using this analysis technique. This issue's collection of essays should help familiarize our readers with this interesting new racehorse in the Machine …
https://www.researchgate.net/publication/221621494_Support_Vector_Machines_Theory_and_Applications
[Show full abstract] utilizing support vector machine (SVM) models for predicting Powered-Two-Wheeler (PTW) accident risk and PTW accident type propensity on urban arterials. The proposed ...
http://onlinelibrary.wiley.com/doi/10.1002/widm.1125/abstract
Apr 28, 2014 · Abstract. This paper provides an overview of the support vector machine (SVM) methodology and its applicability to real-world engineering problems. Specifically, the aim of this study is to review the current state of the SVM technique, and to show some of its latest successful results in real-world problems present in different engineering fields.
https://www.sciencedirect.com/topics/neuroscience/support-vector-machines
Abstract. Support Vector Machines (SVMs) and Kernel methods have found a natural and effective coexistence since their introduction in the early 90s. In this article, we will describe the main concepts that motivate the importance of this relationship. In fact SVMs use kernels for learning linear predictors in high dimensional feature spaces.
https://www.sciencedirect.com/topics/neuroscience/support-vector-machine
Raoof Gholami, Nikoo Fakhari, in Handbook of Neural Computation, 2017. Abstract. Support Vector Machine (SVM) has been introduced in the late 1990s and successfully applied to many engineering related applications. In this chapter, attempts were made …
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