Title :
Research of Attributes Discretization Based on Granular Entropy Considering the Discrimination of Rough Set
Author_Institution :
Sch. of Inf. Eng., Tianjin Univ. of Commerce, Tianjin, China
Abstract :
Attributes discretization is an important and difficult step in the data pretreatment for data mining. In order to overcome the defect that row-column measure is affected by the position of attributes and breakpoints, an approach for attributes discretization based on granular entropy considering discrimination was proposed. The approach searches the optimal discretization breakpoints sets in information table according to the characters of granular entropy and equivalence relation of rough set. And moreover, the feasibility and validity of algorithm was showed by the testing data.
Keywords :
data mining; entropy; rough set theory; attributes discretization; data mining; data pretreatment; data testing; granular entropy; optimal discretization breakpoints sets; rough set discrimination; Business; Data engineering; Data mining; Electronic mail; Entropy; Intelligent networks; Intelligent systems; Position measurement; Set theory; Testing; attributes discretization; equivalence relation; granular entropy; rough set;
Conference_Titel :
Intelligent Networks and Intelligent Systems, 2009. ICINIS '09. Second International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-5557-7
Electronic_ISBN :
978-0-7695-3852-5
DOI :
10.1109/ICINIS.2009.140