Title of article
Learning Bayesian networks for clustering by means of constructive induction
Author/Authors
Lozano، J.A. نويسنده , , Larranaga، P. نويسنده , , Pena، J.M. نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 1999
Pages
-1218
From page
1219
To page
0
Abstract
Atesselation (sigma) is called strongly normal, if it is normal (topological discs with intersections that are either empty or connected) and for any subset of cells C1.....,C(K), C* of the tesselation holds: if the intersection (intersection k i=1) C(i), of all C(i), is nonempty and each C, has nonempty intersection with C*, then the intersection C* intersection intersection k i=1) C(i), of all C, with C* is nonempty. This concept was introduced for polygonal or polyhedral cells in a recent paper by Saha and Rosenfeld, where they proved that it is equivalent to the topological property that any cell together with any set of neighbouring cells forms a simply connected set. Answering a question from their paper, it is shown here that at least in the plane the cells need not be convex polygons, but can be arbitrary topological discs. Also the property is already implied if all collections of three cells have this property, giving a simpler characterization and a connection to Helly-type theorems.
Keywords
Clustering , Bayesian networks , Learning from incomplete data , Constructive induction , EM algorithm , Bound and Collapse method , Simulated annealing
Journal title
PATTERN RECOGNITION LETTERS
Serial Year
1999
Journal title
PATTERN RECOGNITION LETTERS
Record number
14897
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