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http://ivanciuc.org/Files/Reprint/Ivanciuc_Applications_of_Support_Vector_Machines_in_Chemistry.pdf
Applications of Support Vector Machines in Chemistry Ovidiu Ivanciuc Sealy Center for Structural Biology, Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas INTRODUCTION Kernel-based techniques (such as …
https://en.wikipedia.org/wiki/Support-vector_machine
The soft-margin support vector machine described above is an example of an empirical risk minimization (ERM) algorithm for the hinge loss. Seen this way, support vector machines belong to a natural class of algorithms for statistical inference, and many of its unique features are due to …
https://www.sciencedirect.com/science/article/pii/S0169743908001998
Support vector machines are becoming increasingly popular in dealing with either classification or regression problem. Firmly rooted in the VC theory in the field of machine learning, this method was originally developed for the classification problem by Vapnik and the coworkers.Cited by: 299
https://pubs.acs.org/doi/10.1021/acs.analchem.5b03113
Proteomic and metabolomic studies based on chemical profiling require powerful classifiers to model accurately complex collections of data. Support vector machines (SVMs) are advantageous in that they provide a maximum margin of separation for the classification hyperplane. A new method for constructing classification trees, for which the branches comprise SVMs, has been devised. The novel ...Cited by: 18
https://www.semanticscholar.org/paper/Applications-of-Support-Vector-Machines-in-Ivanciuc/572d3c5fe5a2908d308701fc88dc4484d44fba14
Kernel-based techniques (such as support vector machines, Bayes point machines, kernel principal component analysis, and Gaussian processes) represent a major development in machine learning algorithms. Support vector machines (SVM) are a group of supervised learning methods that can be applied to classification or regression. In a short period of time, SVM found numerous applications in ...
http://support-vector-machines.org/SVM_review.html
SVM, support vector machines, SVMC, support vector machines classification, SVMR, support vector machines regression, kernel, machine learning, pattern recognition ...
http://support-vector-machines.org/
Kernel-based techniques (such as support vector machines, Bayes point machines, kernel principal component analysis, and Gaussian processes) represent a major development in machine learning algorithms. Support vector machines (SVM) are a group of supervised learning methods that can be applied to classification or regression.
https://pubs.rsc.org/en/content/articlelanding/2011/an/c0an00387e#!
Support vector machine regression (SVR/LS-SVM)—an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data . Roman M. Balabin* a and Ekaterina I. Lomakina b Author affiliations ...
http://www.cbs.dtu.dk/courses/27623.algo/material/SVM/Ivanciuc_SVM_CCR_2007_23_291.pdf
Application s o f Support Vector Machine s in Chem istry Ovidiu Ivanciuc Sealy Center for Structural Biology , Department of Biochemi stry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas INTRODUCTION Kernel -based techniq ues (such as supp ort vect or …
https://pubs.acs.org/doi/10.1021/ci049877y
Sep 14, 2004 · Support vector machine (SVM), as a novel type of learning machine, for the first time, was used to develop a predictive model for early diagnosis of anorexia. It was based on the concentration of six elements (Zn, Fe, Mg, Cu, Ca, and Mn) and the age extracted from 90 cases. Compared with the results obtained from two other classifiers, partial least squares (PLS) and back-propagation neural ...
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