Title :
Obtaining a Linguistically Understandable Random Sets-Based Classifier from Interval-Valued Data with Genetic Algorithms
Author :
Sanchez, L. ; Couso, Inés
Author_Institution :
Univ. de Oviedo, Oviedo, Spain
fDate :
Nov. 30 2009-Dec. 2 2009
Abstract :
Combining descent algorithms and a coevolutionary scheme, we have defined a new procedure that is able to obtain rule-based models from datasets with censored or interval-valued data, and can also identify the conflictive instances in the training set: those that contribute the most to the indetermination in the likelihood of the model.
Keywords :
genetic algorithms; knowledge based systems; random processes; set theory; coevolutionary scheme; descent algorithms; genetic algorithms; interval-valued data; linguistically understandable random sets-based classifier; rule-based models; Fuzzy logic; Fuzzy sets; Fuzzy systems; Genetic algorithms; Intelligent systems; Knowledge based systems; Maximum likelihood estimation; Parametric statistics; State estimation;
Conference_Titel :
Intelligent Systems Design and Applications, 2009. ISDA '09. Ninth International Conference on
Conference_Location :
Pisa
Print_ISBN :
978-1-4244-4735-0
Electronic_ISBN :
978-0-7695-3872-3
DOI :
10.1109/ISDA.2009.162
