Title :
The optimal decision rules discovery
Author :
Kou, Huaicheng ; Wu, Yunjie ; Zhao, Lijun
Author_Institution :
Sch. of Autom. Sci. & Electr. Eng., Behang Univ., Beijing, China
Abstract :
Aiming at the data set expressed by decision-list, proposed an algorithm of optimum decision rules discovery based on granule computing. It increased the efficiency of decision rules mining by two ways, improving speed of getting frequent item sets with granule computing and deleting invalid candidate sets. Finally the result of calculating test showed the algorithm is validity.
Keywords :
data mining; decision making; decision tables; decision list; decision rule mining; granule computing; optimal decision rule discovery; Annealing; Educational institutions; Filtering algorithms; Granule Computing; Optimal decision rule; association rule; decision table;
Conference_Titel :
Future Information Technology and Management Engineering (FITME), 2010 International Conference on
Conference_Location :
Changzhou
Print_ISBN :
978-1-4244-9087-5
DOI :
10.1109/FITME.2010.5656313
