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Support Vector Machines and Support Vector Regression [PDF]
, 2022 AbstractIn this chapter, the support vector machines (svm) methods are studied. We first point out the origin and popularity of these methods and then we define the hyperplane concept which is the key for building these methods. We derive methods related to svm: the maximum margin classifier and the support vector classifier. We describe the derivation
Osval A. Montesinos-L֯ópez +2 more
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Functional support vector machine. [PDF]
BiostatisticsAbstract Linear and generalized linear scalar-on-function modeling have been commonly used to understand the relationship between a scalar response variable (e.g. continuous, binary outcomes) and functional predictors. Such techniques are sensitive to model misspecification when the relationship between the response variable and the ...
Xie S, Ogden RT.
europepmc +3 more sources
Global-local least-squares support vector machine (GLocal-LS-SVM)
PLoS ONE, 2023 This study introduces the global-local least-squares support vector machine (GLocal-LS-SVM), a novel machine learning algorithm that combines the strengths of localised and global learning.
Ahmed Youssef Ali Amer
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Efficient heart disease diagnosis based on twin support vector machine
Diagnostyka, 2021 Heart disease is the leading cause of death in the world according to the World Health Organization (WHO). Researchers are more interested in using machine learning techniques to help medical staff diagnose or detect heart disease early.
Youcef Brik +2 more
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Safe transductive support vector machine
Connection Science, 2022 Since semi-supervised learning can use fewer labelled samples to train a better model, semi-supervised methods are becoming popular in data mining. As an important algorithm of semi-supervised support vector machines (S $ ^{3} $ VM), transductive support
Haiyan Chen +3 more
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On Coresets for Support Vector Machines [PDF]
Theoretical Computer Science, 2020 We present an efficient coreset construction algorithm for large-scale Support Vector Machine (SVM) training in Big Data and streaming applications. A coreset is a small, representative subset of the original data points such that a models trained on the coreset are provably competitive with those trained on the original data set. Since the size of the
Murad Tukan +3 more
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Support Vector Machine For Hoax Detection
SINTECH (Science and Information Technology) Journal, 2023 Along with the development of information technology, news media has also developed by presenting information online Along with the rapid development of online news, the spread of fake news information (hoaxes) is also increasing rapidly and widely ...
Ni Wayan Sumartini Saraswati +3 more
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Wavelet Support Vector Machine [PDF]
IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 2004 An admissible support vector (SV) kernel (the wavelet kernel), by which we can construct a wavelet support vector machine (SVM), is presented. The wavelet kernel is a kind of multidimensional wavelet function that can approximate arbitrary nonlinear functions. The existence of wavelet kernels is proven by results of theoretic analysis.
Li, Zhang, Weida, Zhou, Licheng, Jiao
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Binarized Support Vector Machines [PDF]
INFORMS Journal on Computing, 2010 The widely used support vector machine (SVM) method has shown to yield very good results in supervised classification problems. Other methods such as classification trees have become more popular among practitioners than SVM thanks to their interpretability, which is an important issue in data mining.In this work, we propose an SVM-based method that ...
Romero Morales, Dolores +2 more
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Contextualizing Support Vector Machine Predictions
International Journal of Computational Intelligence Systems, 2020 Classification in artificial intelligence is usually understood as a process whereby several objects are evaluated to predict the class(es) those objects belong to.
Marcelo Loor, Guy De Tré
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