Title :
A New Discretization Approach of Continuous Attributes
Author :
Xu, E. ; Liangshan, Shao ; Yongchang, Ren ; Hao, Wu ; Feng, Qiu
Author_Institution :
Electron. & Inf. Eng. Coll., Liaoning Univ. of Technol., Jinzhou, China
Abstract :
To deal with the discretization problem in an information system, a new discretization approach of continuous attributes is proposed in this paper based on the relative entropy and rough set theory. The candidate interval class-information entropy is used to select the threshold boundary for discretization in this method. And the redundant cut points are removed through the inspection of the cut point value of each attribute to discretize the condition attributes and decision attributes in an information system. Experiment results show that the method is simple and effective.
Keywords :
data mining; entropy; information systems; learning (artificial intelligence); rough set theory; continuous attributes; discretization approach; information system; relative entropy; rough set theory; Data mining; Databases; Educational institutions; Information entropy; Information systems; Inspection; Machine learning; Machine learning algorithms; Set theory; Wearable computers; cut points; discretization; information system; relative entropy; rough set theory;
Conference_Titel :
Wearable Computing Systems (APWCS), 2010 Asia-Pacific Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-6467-8
Electronic_ISBN :
978-1-4244-6468-5
DOI :
10.1109/APWCS.2010.40
