DocumentCode :
479098
Title :
Research on Data Mining Algorithms Based on Fuzzy Theory
Author :
Wang, Ai-min ; Yang, Yu-xing ; Yang, Zhi-min
Author_Institution :
Sch. of Comput. & Inf. Eng., Anyang Normal Univ., Anyang
fYear :
2008
fDate :
12-14 Oct. 2008
Firstpage :
1
Lastpage :
4
Abstract :
Data mining is a new filed in data processing research. Support vector machine (SVM) is one of the new methods using in data mining, which has gained great applicable success. However, there are stiff plenty of limitations in SVM. For example, SVM won´t work if its training set contains fuzzy information. In order to solve the problem presented above, this article discusses the constraining programming of uncertain chance and the characteristic of uncertain classification as well as its expression methods. The algorithm for classifying support vector machine is also included in this article.
Keywords :
data mining; fuzzy set theory; support vector machines; data mining algorithms; fuzzy theory; support vector machine; Computer science; Data engineering; Data mining; Data processing; Educational institutions; Fuzzy sets; Linear programming; Machine learning; Support vector machine classification; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-2107-7
Electronic_ISBN :
978-1-4244-2108-4
Type :
conf
DOI :
10.1109/WiCom.2008.2714
Filename :
4680903
Link To Document :
بازگشت