Classification of Multivariate Data Using Distribution Mapping Exponent

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SYSNO ASEP	0405144
Document Type	C - Proceedings Paper (int. conf.)
R&D Document Type	Conference Paper
Title	Classification of Multivariate Data Using Distribution Mapping Exponent
Author(s)	Jiřina, Marcel (UIVT-O)_{SAI, RID}
Source Title	Proceedings of the International Conference in Memoriam John von Neumann / Szakál A.. - Budapest : Budapest Muszaki Foiskola (Budapest Polytechnic), 2003 - ISBN 963-7154-21-3
Pages	s. 155-168
Number of pages	14 s.
Action	International Conference in Memorial John von Neumann
Event date	12.12.2003
VEvent location	Budapest
Country	HU - Hungary
Event type	WRD
Language	eng - English
Country	HU - Hungary
Keywords	multivariate data ; classification ; distribution mapping exponent
Subject RIV	BA - General Mathematics
R&D Projects	LN00B096 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
Annotation	We introduce distribution-mapping exponent that is something like effective dimensionality of multidimensional space. The method for classification of multivariate data is based on local estimate of distribution mapping exponent q for each point x. It is shown that the sum of reciprocals of q-th power of distances of all points of a given class can be used as the probability density estimate.
Workplace	Institute of Computer Science
Contact	Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
Year of Publishing	2004

Number of the records: 1