DocumentCode
1807111
Title
A Method of Dealing with Numeric Attribute Based on Sample Distribution
Author
Zhu, Weidong ; Lin, Yongmin
Author_Institution
Sch. of Comput. & Inf. Technol., Beijing Jiaotong Univ., Beijing, China
fYear
2010
fDate
24-25 July 2010
Firstpage
240
Lastpage
243
Abstract
In order to improve the predictive accuracy of inductive learning, a heavy analysis about the demerit of C4.5 in dealing with numeric attribute is given. By the method of estimating the probability distribution of the training samples, a new and simple method of dealing with numeric attribute is proposed in this paper. Experimental results of UCI data sets show that the proposed method has an excellent performance on accuracy issue and faster computing speed than C4.5 algorithm.
Keywords
decision trees; learning by example; probability; C4.5 algorithm; inductive learning; numeric attribute; probability distribution estimation; sample distribution; Accuracy; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Data mining; Entropy; Error analysis; distribution of training samples; entropy; numeric attribute;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology and Computer Science (ITCS), 2010 Second International Conference on
Conference_Location
Kiev
Print_ISBN
978-1-4244-7293-2
Electronic_ISBN
978-1-4244-7294-9
Type
conf
DOI
10.1109/ITCS.2010.65
Filename
5557140
Link To Document