Title :
Sequential Pattern Recognition: Naive Bayes Versus Fuzzy Relation Method
Author :
Kurzynski, Marek ; Zolnierek, Andrzej
Author_Institution :
Fac. of Electron., Wroclaw Univ. of Technol.
Abstract :
In this paper two possibilities of taking into account the dependencies in the sequential pattern recognition task are considered. The first method is naive Bayes attempt adopted to the probabilistic model of sequential decision problem in which, the assumption of Markov dependence in the sequence of recognized patterns is made. The second one is the fuzzy relation approach, in which we omitted such not necessary correct assumptions. Furthermore, both methods were applied to the medical diagnostic task and the results of computer investigations are discussed
Keywords :
Bayes methods; Markov processes; decision theory; fuzzy set theory; medical diagnostic computing; pattern recognition; probability; Bayes method; Markov dependence; fuzzy relation method; medical diagnostic task; probabilistic model; sequential decision problem; sequential pattern recognition; Computer networks; Context modeling; Current measurement; Diseases; Fuzzy systems; Inference algorithms; Mathematical model; Medical diagnosis; Medical treatment; Pattern recognition;
Conference_Titel :
Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-7695-2504-0
DOI :
10.1109/CIMCA.2005.1631420