Title :
Knowledge Discovery of Classification Based on Cloud Model and Genetic Algorithm
Author :
Hesong, Li ; Guangwei, Zhang ; Deyi, Li ; Xiangmei, Li
Author_Institution :
Beihang Univ., Beijing
Abstract :
As an important branch of Knowledge Discovery, the task of Data Classification is to determine the objects that belong to which pre-defined goals. As evolutionary computation does not require priori assumptions, it shows great vitality in dealing with imprecise, incomplete and uncertain information, which the traditional methods of statistical classifications are helpless in the classification issues. This paper presents a classification algorithm based on cloud model and genetic algorithm. Experiments show that the algorithm is efficient to continuous attribute data sets for the classification.
Keywords :
data mining; genetic algorithms; pattern classification; cloud model; data classification; evolutionary computation; genetic algorithm; incomplete information; knowledge discovery; statistical classifications; uncertain information; Character generation; Classification algorithms; Clouds; Data mining; Displacement measurement; Entropy; Evolutionary computation; Genetic algorithms; Helium; Position measurement; Classification; Cloud Evolution; Cloud Model; Genetic Algorithm;
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
DOI :
10.1109/CSSE.2008.821