Title :
Data-driven decision tree learning algorithm based on rough set theory
Author :
Yin, Desheng ; Wang, Guoyin ; Wu, Yu
Author_Institution :
Inst. of Comput. Sci. & Technol., Chongqing Univ. of Posts & Telecommun., China
Abstract :
Decision tree pre-pruning is an effective method to solve the over-fitting problem in decision tree learning process. However, it is difficult to estimate the exact time to stop the growing process of a decision tree, which limits the developments and applications of this method. In this paper, the growing of a decision tree is controlled by the uncertainty of a decision table, and a data-driven learning algorithm for decision tree pre-pruning is developed.
Keywords :
data mining; decision tables; decision trees; learning (artificial intelligence); rough set theory; data-driven decision tree learning algorithm; decision table uncertainty; decision tree prepruning; rough set theory; Automatic control; Computer science; Decision trees; Knowledge acquisition; Machine learning algorithms; Measurement uncertainty; Process control; Set theory; Testing; Training data;
Conference_Titel :
Active Media Technology, 2005. (AMT 2005). Proceedings of the 2005 International Conference on
Print_ISBN :
0-7803-9035-0
DOI :
10.1109/AMT.2005.1505426
