Title :
Study of CS-GE Classification Algorithm
Author :
Song, DingLi ; Yang, Bingru ; Wang, Aichun
Author_Institution :
Sch. of Inf. Eng., Univ. of Sci. & Technol. Beijing, Beijing, China
Abstract :
In data mining, the classification algorithms usually pursue more highly accuracy. It is based on the assumption that all misclassifications have the same cost. Obvious, the assumption is not suitable. By improving the encode/decode methods and taking different misclassification cost into account, this paper concerns a new cost-sensitive algorithm called CS-GE based on Gene Expression. The experimental results show that the new algorithm is effective.
Keywords :
data mining; genetic algorithms; pattern classification; CS-GE classification algorithm; data mining; encode-decode methods; gene expression; Accuracy; Algorithm design and analysis; Classification algorithms; Diseases; Genetics; Heart; Training; CS-GE; classification; cost of misclassification; cost-sensitive;
Conference_Titel :
Electrical and Control Engineering (ICECE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6880-5
DOI :
10.1109/iCECE.2010.1034
