TY - GEN
T1 - Constructing the shortest ECOC for fast multi-classification
AU - Li, Jianwu
AU - Wei, Haizhou
AU - Yan, Ziye
PY - 2011
Y1 - 2011
N2 - Error-correcting output codes (ECOC) is an effective method to perform multi-classification via decomposing a multi-classification problem into many binary classification tasks, and then integrating the outputs of the subtasks into a whole decision. The researches on applying ECOC to multi-classification mainly focus on how to improve the correcting ability of output codes and how to enhance the classification effectiveness of ECOC. This paper addresses a simple but interesting and significant case of ECOC, the shortest ECOC, to perform fast multi-classification at the cost of sacrificing a very small classification precision. The strategy of balancing the positive and negative examples for each binary classifier of ECOC and the method of finding the optimal permutation of all original classes are further given. Preliminary experimental results show, the shortest ECOC uses fewest binary classifiers but can still obtain comparable or close classification precisions with several traditional encoding methods of ECOC.
AB - Error-correcting output codes (ECOC) is an effective method to perform multi-classification via decomposing a multi-classification problem into many binary classification tasks, and then integrating the outputs of the subtasks into a whole decision. The researches on applying ECOC to multi-classification mainly focus on how to improve the correcting ability of output codes and how to enhance the classification effectiveness of ECOC. This paper addresses a simple but interesting and significant case of ECOC, the shortest ECOC, to perform fast multi-classification at the cost of sacrificing a very small classification precision. The strategy of balancing the positive and negative examples for each binary classifier of ECOC and the method of finding the optimal permutation of all original classes are further given. Preliminary experimental results show, the shortest ECOC uses fewest binary classifiers but can still obtain comparable or close classification precisions with several traditional encoding methods of ECOC.
KW - Error-correcting output codes
KW - multi-classification
KW - shortest encoding strategy
KW - support vector machines
UR - http://www.scopus.com/inward/record.url?scp=84863251044&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-25975-3_41
DO - 10.1007/978-3-642-25975-3_41
M3 - Conference contribution
AN - SCOPUS:84863251044
SN - 9783642259746
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 462
EP - 471
BT - Knowledge Science, Engineering and Management - 5th International Conference, KSEM 2011, Proceedings
T2 - 5th International Conference on Knowledge Science, Engineering and Management, KSEM 2011
Y2 - 12 December 2011 through 14 December 2011
ER -