Doktorandské dny 2007. - Praha : Česká technika ČVUT, 2007
- ISBN 978-80-01-03913-7
S. 57-66
Poč.str.
10 s.
Akce
Doktorandské dny 2007
Datum konání
16.11.2007
Místo konání
Praha
Země
CZ - Česká republika
Typ akce
CST
Jazyk dok.
eng - angličtina
Země vyd.
CZ - Česká republika
Klíč. slova
EM algorithm ; distribution mixtures ; cluster analysis ; cathegorial data
Vědní obor RIV
BB - Aplikovaná statistika, operační výzkum
CEP
GA102/07/1594 GA ČR - Grantová agentura ČR
1M0572 GA MŠMT - Ministerstvo školství, mládeže a tělovýchovy
CEZ
AV0Z10750506 - UTIA-B (2005-2011)
Anotace
The EM algorithm has been used repeatedly to identify latent classes in categorical data by estimating finite distribution mixtures of product 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. As such a mixture we use also an optimally smoothed kernel estimate. 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.
