TY - GEN
T1 - Function Sequence Genetic Programming for pattern classification
AU - Wang, Shixian
AU - Zhao, Qingjie
AU - Chen, Yuehui
AU - Wu, Peng
PY - 2011
Y1 - 2011
N2 - Pattern classification is one of the most researched problems in Artificial Intelligence. Genetic Programming (GP) has been used to construct classifiers by many researchers. Function Sequence Genetic Programming (FSGP) is a new variant of GP, base on which constructing classifier has not been investigated now. This paper explores the application of FSGP to pattern classification. Base on FSGP, binary classifier and multi-classifier are constructed. Experiments on four well-known data sets are made to demonstrate the classification performance of FSGP.
AB - Pattern classification is one of the most researched problems in Artificial Intelligence. Genetic Programming (GP) has been used to construct classifiers by many researchers. Function Sequence Genetic Programming (FSGP) is a new variant of GP, base on which constructing classifier has not been investigated now. This paper explores the application of FSGP to pattern classification. Base on FSGP, binary classifier and multi-classifier are constructed. Experiments on four well-known data sets are made to demonstrate the classification performance of FSGP.
KW - Function Sequence Genetic Programming(FSGP)
KW - Genetic program-ming(GP)
KW - Pattern Classification
UR - https://www.scopus.com/pages/publications/80053430215
U2 - 10.1109/ICNC.2011.6022170
DO - 10.1109/ICNC.2011.6022170
M3 - Conference contribution
AN - SCOPUS:80053430215
SN - 9781424499533
T3 - Proceedings - 2011 7th International Conference on Natural Computation, ICNC 2011
SP - 1092
EP - 1096
BT - Proceedings - 2011 7th International Conference on Natural Computation, ICNC 2011
T2 - 2011 7th International Conference on Natural Computation, ICNC 2011
Y2 - 26 July 2011 through 28 July 2011
ER -