Classification Using the Zipfian Kernel

Marcel Jiřina () and Marcel Jiřina ()

Journal of Classification, 2015, vol. 32, issue 2, 305-326

Abstract: We propose to use the Zipfian distribution as a kernel for the design of a nonparametric classifier in contrast to the Gaussian distribution used in most kernel methods. We show that the Zipfian distribution takes into account multifractal nature of data and gives a true picture of scaling properties inherent in data. We also show that this new look at data structure can lead to a simple classifier that can, for some tasks, outperform more complex systems. Copyright Classification Society of North America 2015

Keywords: Kernel machine; Zipfian kernel; Multivariate data; Correlation dimension; Harmonic series; Classification (search for similar items in EconPapers)
Date: 2015
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1007/s00357-015-9174-2 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jclass:v:32:y:2015:i:2:p:305-326

Ordering information: This journal article can be ordered from
http://www.springer. ... hods/journal/357/PS2

DOI: 10.1007/s00357-015-9174-2

Access Statistics for this article

Journal of Classification is currently edited by Douglas Steinley

More articles in Journal of Classification from Springer, The Classification Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().