Results 11 to 20 of about 350,996 (311)

Binarized Support Vector Machines [PDF]

open access: yesINFORMS 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 ...
Emilio Carrizosa   +2 more
openaire   +9 more sources

Wavelet Support Vector Machine [PDF]

open access: yesIEEE Transactions on Systems, Man, and 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, Licheng Jiao, Weida Zhou
exaly   +3 more sources

Support Vector Machines inR [PDF]

open access: yesJournal of Statistical Software, 2006
Being among the most popular and efficient classification and regression methods currently available, implementations of support vector machines exist in almost every popular programming language. Currently four R packages contain SVM related software. The purpose of this paper is to present and compare these implementations.
Karatzoglou, Alexandros   +2 more
core   +11 more sources

Functional support vector machine. [PDF]

open access: yesBiostatistics
Abstract 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

On Coresets for Support Vector Machines [PDF]

open access: yesTheoretical 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
openaire   +4 more sources

Global-local least-squares support vector machine (GLocal-LS-SVM)

open access: yesPLoS 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
doaj   +2 more sources

Support Vector Machines [PDF]

open access: yesThe Stata Journal: Promoting communications on statistics and Stata, 2016
Support vector machines are statistical- and machine-learning techniques with the primary goal of prediction. They can be applied to continuous, binary, and categorical outcomes analogous to Gaussian, logistic, and multinomial regression. We introduce a new command for this purpose, svmachines.
Guenther, Nick, Schonlau, Matthias
openaire   +1 more source

Efficient heart disease diagnosis based on twin support vector machine

open access: yesDiagnostyka, 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
doaj   +1 more source

Safe transductive support vector machine

open access: yesConnection 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
doaj   +1 more source

Properties of Support Vector Machines [PDF]

open access: yesNeural Computation, 1998
Support vector machines (SVMs) perform pattern recognition between two point classes by finding a decision surface determined by certain points of the training set, termed support vectors (SV). This surface, which in some feature space of possibly infinite dimension can be regarded as a hyperplane, is obtained from the solution of a problem of ...
PONTIL M, VERRI, ALESSANDRO
openaire   +3 more sources

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