A robust approach to empirical PDF estimate

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This paper presents a robust approach to estimate the probability density function (PDF) from a sample data set. The approach is induced from entropy maximization using Renyi's quadratic entropy, and turns out to be equivalent to the support vector machines (SVM). Therefore, the approach has good properties of the support vector machines as a statistical function estimation method. (c) 2005 Published by Elsevier B.V.
Publisher
ELSEVIER SCIENCE BV
Issue Date
2005-08
Language
English
Article Type
Article
Citation

NEUROCOMPUTING, v.67, pp.288 - 296

ISSN
0925-2312
DOI
10.1016/j.neucom.2005.01.005
URI
http://hdl.handle.net/10203/88156
Appears in Collection
CS-Journal Papers(저널논문)
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