DocumentCode :
690435
Title :
A Method of Discretization of Continuous Attributes in Knowledge Discovery
Author :
Xuequan Tian
Author_Institution :
Chongqing Univ. of Sci. & Technol., Chongqing, China
fYear :
2013
fDate :
14-15 Dec. 2013
Firstpage :
695
Lastpage :
698
Abstract :
Discretization of continuous attributes is an important preprocessing step in knowledge discovery. Most consecutive property boundaries are blurred. It is suitable for soft classification. This paper introduced the fuzzy set of continuous attribute values are transformed into fuzzy attribute values. We presents the discretization method based on fuzzy similarity clustering. The experiment shows the method of discretization is more effective and objective than others. It is a effective method in discretization of the continuous attribute.
Keywords :
data mining; fuzzy set theory; pattern classification; pattern clustering; consecutive property boundaries; continuous attribute values; discretization method; fuzzy attribute values; fuzzy set; fuzzy similarity clustering; knowledge discovery; soft classification; Complexity theory; Computers; Educational institutions; Information systems; Knowledge discovery; Pattern recognition; Set theory; Continuous Attributes; Discretization; Fuzzy Clustering; Knowledge Discovery;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Sciences and Applications (CSA), 2013 International Conference on
Conference_Location :
Wuhan
Type :
conf
DOI :
10.1109/CSA.2013.167
Filename :
6835693
Link To Document :
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