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URN etd-0616104-161011 Statistics This thesis had been viewed 3315 times. Download 1504 times. Author Wen-Ke Tseng Author's Email Address No Public. Department Information Management Year 2003 Semester 2 Degree Master Type of Document Master's Thesis Language English Page Count 50 Title A Heuristic Partition Method of Numerical Attributes in Classification Tree Construction Keyword Numerical Attribute ID3 Algorithm Classification Tree C4.5 Algorithm C4.5 Algorithm Classification Tree ID3 Algorithm Numerical Attribute Abstract Inductive Learning, a kind of learning methods, has been applied extensively in Machine Learning. Thus, Classification tree is a well-known method in Inductive Learning. The ID3, a popular classification tree algorithm, had been proposed by Quinlan on 1986. Quinlan proposed the C4.5 algorithm on 1993 again. The C4.5 has not been efficiently searching the splitting points on numerical attributes. Therefore, some researchers had proposed improved approaches and new partition methods for the partition on numerical attributes. However, these approaches and methods have its assumptions and restrictions. So we have proposed a heuristic partition method to improve the defect, which the C4.5 algorithm could not process numerical attributes efficiently. Since the heuristic partition method is based on C4.5 algorithm, the method can greatly reduce the time for searching splitting point on numerical attributes. Advisor Committee Ester Yen - advisor
Yen-Ju Yang - advisor
Huei-Huang Chen - co-chair
Files Date of Defense 2004-06-08 Date of Submission 2004-06-16