TY - GEN
T1 - Simplify multi-valued decision trees
AU - Liu, Chien-Liang
AU - Lee, Chia-Hoang
PY - 2008/12/19
Y1 - 2008/12/19
N2 - Decision tree is one of the popular data mining algorithms and it has been applied on many classification application areas. In many applications, the number of attribute values may be over hundreds and that will be difficult to analyze the result. The purpose of this paper will focus on the construction of categorical decision trees. A binary splitting decision tree algorithm is proposed to simplify the classification outcomes. It adopts the complement operation to simplify the split of interior nodes and it is suitable to apply on the decision trees where the number of outcomes is numerous. In addition, meta-attribute could be applied on some applications where the number of outcomes is numerous and the meta-attribute is meaningful. The benefit of meta-attribute representation is that it could transfer the original attributes into higher level concepts and that could reduce the number of outcomes.
AB - Decision tree is one of the popular data mining algorithms and it has been applied on many classification application areas. In many applications, the number of attribute values may be over hundreds and that will be difficult to analyze the result. The purpose of this paper will focus on the construction of categorical decision trees. A binary splitting decision tree algorithm is proposed to simplify the classification outcomes. It adopts the complement operation to simplify the split of interior nodes and it is suitable to apply on the decision trees where the number of outcomes is numerous. In addition, meta-attribute could be applied on some applications where the number of outcomes is numerous and the meta-attribute is meaningful. The benefit of meta-attribute representation is that it could transfer the original attributes into higher level concepts and that could reduce the number of outcomes.
UR - http://www.scopus.com/inward/record.url?scp=58549101548&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-92137-0_64
DO - 10.1007/978-3-540-92137-0_64
M3 - Conference contribution
AN - SCOPUS:58549101548
SN - 3540921362
SN - 9783540921363
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 581
EP - 590
BT - Advances in Computation and Intelligence - Third International Symposium, ISICA 2008, Proceedings
T2 - 3rd International Symposium on Intelligence Computation and Applications, ISICA 2008
Y2 - 19 December 2008 through 21 December 2008
ER -