@article{vsvm,
title = {A tutorial on \ν-support vector machines: Research Articles},
address = {Chichester, UK, UK},
author = {Pai-Hsuen Chen and Chih-Jen Lin and Bernhard Sch\"{o}lkopf},
journal = {Appl. Stoch. Model. Bus. Ind.},
number = {2},
pages = {111--136},
publisher = {John Wiley and Sons Ltd.},
url = {http://vis.lbl.gov/~romano/mlgroup/papers/nusvmtutorial.pdf},
volume = {21},
year = {2005},
description = {A tutorial on ν-support vector machines},
abstract = {We briefly describe the main ideas of statistical learning theory, support vector machines (SVMs), and kernel feature spaces. We place particular emphasis on a description of the so-called ν-SVM, including details of the algorithm and its implementation, theoretical results, and practical applications. Copyright © 2005 John Wiley & Sons, Ltd.Parts of the present article are based on [1].},
issn = {1524-1904}, doi = {http://dx.doi.org/10.1002/asmb.v21:2},
keywords = {kernel svm trick tutorial }
}
::