Minimum Information Loss Cluster Analysis for Cathegorical Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F07%3A00086490" target="_blank" >RIV/67985556:_____/07:00086490 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Minimum Information Loss Cluster Analysis for Cathegorical Data
Original language description
The EM algorithm has been used repeatedly to identify latent classes in categorical data by estimating finite distribution mixtures of produkt components. Unfortunately, the underlying mixtures are not uniquely identifiable and, moreover, the estimated mixture parameters are starting-point dependent. For this reason we use the latent class model only to define a set of ``elementary'' classes by estimating a mixture of a large number components. We propose a hierarchical ``bottom up'' cluster analysis based on unifying the elementary latent classes sequentially. The clustering procedure is controlled by minimum information loss criterion.
Czech name
Shluková analýza kategoriálních dat s minimální ztrátou informace
Czech description
Shluková analýza kategoriálních dat s využitím kriteria minimální ztráty informace.
Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BD - Information theory
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2007
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Lecture Notes in Computer Science
ISSN
0302-9743
e-ISSN
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Volume of the periodical
2007
Issue of the periodical within the volume
4571
Country of publishing house
DE - GERMANY
Number of pages
15
Pages from-to
233-247
UT code for WoS article
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EID of the result in the Scopus database
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