| Título: | Application Of t-Cherry Junction Trees in Pattern Recognition |
| Autores: |
Tamas Szantai; Institute of Mathematics Budapest University of Technology and Economics Edith Kovacs; Budapest College of Management |
| Fecha: | 2010-06-04 |
| Publicador: | BRAIN: Broad Research in Artificial Intelligence and Neuroscience |
| Fuente: |
 |
| Tipo: | |
| Tema: |
Artificial Intelligence pattern recognition, probabilistic modeling, h-uniform hyper- tree, t-cherry junction tree 2000 Mathematics Subject Classification: 05C65, 62H30, 68T10, 62P10 |
| Descripción: | Pattern recognition aims to classify data (patterns) based ei-ther on a priori knowledge or on statistical information extracted from the data. In this paper we will concentrate on statistical pattern recognition using a new probabilistic approach which makes possible to select the so called 'informative' features. We develop a pattern recognition algorithm which is based on the conditional independence structure underlying the statistical data. Our method was succesfully applied on a real problem of recognizing Parkinson's disease on the basis of voice disorders. |
| Idioma: | Inglés |
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