The Research of Algorithm for Data Mining Based on Fuzzy Theory
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 still plenty of limitations in SVM. For example, SVM won’t work if its training set contains uncertain in...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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IFSA Publishing, S.L.
2014-04-01
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| Series: | Sensors & Transducers |
| Subjects: | |
| Online Access: | http://www.sensorsportal.com/HTML/DIGEST/april_2014/Vol_168/P_1954.pdf |
| Summary: | 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 still plenty of limitations in SVM. For example, SVM won’t work if its training set contains uncertain information. In order to solve the problem presented above, this paper discusses the constraining programming of fuzzy chance and the characteristic of fuzzy classification as well as its expression methods. The algorithm for classifying Support Vector Machine is also included in this paper. |
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| ISSN: | 2306-8515 1726-5479 |