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

fYear

2010

fDate

17-18 April 2010

Firstpage

136

Lastpage

138

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/APWCS.2010.40

Filename

5481228