Title :
Notice of Retraction
Customer´ credit sale risk classification based on support vector machine and rough sets
Author_Institution :
Sch. of Economic & Manage., Henan Polytech. Univ., Jiaozuo, China
Abstract :
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Aiming at the shortages of the existing data-mining model for classification of customer´s credit sale risk, a new classification model based on rough sets and support vector machine presents is put forward in this paper. First, the theory of rough set is applied to pick up and reduce the index attributes. Then, the training samples are sent to the support vector machine to train and learn. After that, the sorts of the customers´ credit sale risk in test samples are differentiated. The test results indicate that the new classification model based on rough sets and support vector machine shows higher forecast precision than the traditional ones and it is more efficient and practical.
Keywords :
data mining; financial data processing; retail data processing; rough set theory; support vector machines; customer credit sale risk classification model; data mining model; higher forecast precision; rough set theory; support vector machine; Accuracy; Lead; SVM; credit sale; multi-classification; rough set; statistical learning theory;
Conference_Titel :
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-5537-9
DOI :
10.1109/ICCSIT.2010.5563677
