Title :
New decision tree based on genetic algorithm
Author :
Yang, Shiueng-Bien ; Yang, Shen-I
Author_Institution :
Dept. of Inf. Manage. & Commun., Wenzao Ursuline Coll. of Languages, Kaohsiung, Taiwan
Abstract :
The decision tree based on the k-means algorithm has recently been proposed. However, the drawback of the k-means algorithm is that the users must determine the number of branches for each node before the decision tree is designed. The users are usually hard to determine the number of branches for each node. In this study, the new decision tree with variable-branches is proposed. The genetic algorithm is proposed to determine the number of branches for each node in the new decision tree. Thus, the proposed new decision tree approaches to near-optimization.
Keywords :
decision trees; genetic algorithms; pattern clustering; decision tree; genetic algorithm; k-means algorithm; Algorithm design and analysis; Automatic control; Automation; Classification tree analysis; Communication system control; Decision trees; Error analysis; Fuzzy sets; Genetic algorithms; Machine learning; Decision tree; Genetic algorithm; K-means algorithm;
Conference_Titel :
Computer Communication Control and Automation (3CA), 2010 International Symposium on
Conference_Location :
Tainan
Print_ISBN :
978-1-4244-5565-2
DOI :
10.1109/3CA.2010.5533877