Jornal article

Grim J., Hora J.

Lecture Notes in Computer Science

2007

233-247

0302-9743

Ing. Jiří Grim, CSc. (ÚTIA - Oddělení rozpoznávání obrazů)

Cluster Analysis, Cathegorical Data, EM algorithm

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.