TY - GEN
T1 - An evolutionary and attribute-oriented ensemble classifier
AU - Lee, Chien I.
AU - Tsai, Cheng Jung
AU - Ku, Chih Wei
PY - 2006/1/1
Y1 - 2006/1/1
N2 - In the research area of decision tree, numerous researchers have been focusing on improving the predictive accuracy. However, obvious improvement can hardly be made until the introduction of the ensemble classifier. In this paper, we propose an Evolutionary Attribute-Oriented Ensemble Classifier (EAOEC) to improve the accuracy of sub-classifiers and at the same time maintain the diversity among them. EAOEC uses the idea of evolution to choose proper attribute subset for the building of every sub-classifier. To avoid the huge computation cost for the evolution, EAOEC uses the gini value gained during the construction of a sub-tree as the evolution basis to build the next sub-tree. Eventually, EAOEC classifier uses uniform weight voting to combine all sub-classifiers and experiments show that EAOEC can efficiently improve the predictive accuracy.
AB - In the research area of decision tree, numerous researchers have been focusing on improving the predictive accuracy. However, obvious improvement can hardly be made until the introduction of the ensemble classifier. In this paper, we propose an Evolutionary Attribute-Oriented Ensemble Classifier (EAOEC) to improve the accuracy of sub-classifiers and at the same time maintain the diversity among them. EAOEC uses the idea of evolution to choose proper attribute subset for the building of every sub-classifier. To avoid the huge computation cost for the evolution, EAOEC uses the gini value gained during the construction of a sub-tree as the evolution basis to build the next sub-tree. Eventually, EAOEC classifier uses uniform weight voting to combine all sub-classifiers and experiments show that EAOEC can efficiently improve the predictive accuracy.
UR - http://www.scopus.com/inward/record.url?scp=33745922861&partnerID=8YFLogxK
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U2 - 10.1007/11751588_128
DO - 10.1007/11751588_128
M3 - Conference contribution
AN - SCOPUS:33745922861
SN - 3540340726
SN - 9783540340720
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1210
EP - 1218
BT - Computational Science and Its Applications - ICCSA 2006
PB - Springer Verlag
T2 - ICCSA 2006: International Conference on Computational Science and Its Applications
Y2 - 8 May 2006 through 11 May 2006
ER -