Title :
Conditional independence based learning of bayesian classifiers guided by a variable ordering genetic search
Author :
Santos, Edimilson Batista dos ; Hruschka, Estevam R. ; Nicoletti, Maria Do Carmo
Author_Institution :
Fed. Univ. of Sao Carlos, Sao Carlos
Abstract :
This work proposes a genetic strategy for learning a Bayesian classifier using an algorithm based on conditional independence and the information given by a variable ordering. The strategy has been implemented as the system VOGAC-PC. The paper presents and analyses the results of experiments in various domains using VOGAC-PC as well as a previous system, named VOGA-K2, based on algorithm K2.
Keywords :
Bayes methods; genetic algorithms; learning (artificial intelligence); pattern classification; search problems; Bayesian classifier; conditional independence; genetic strategy; learning algorithm; variable ordering genetic search; Bayesian methods; Biological cells; Convergence; Evolutionary computation; Flowcharts; Genetics; Iris;
Conference_Titel :
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1339-3
Electronic_ISBN :
978-1-4244-1340-9
DOI :
10.1109/CEC.2007.4424641
