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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Horng-Lin Shieh Po-Lun Chang |
| Copyright Year | 2010 |
| Description | Author affiliation: Department of Electrical Engineering, Saint John's University, Taipei, Taiwan (Horng-Lin Shieh) || Department of Electrical Engineering, Lunghwa University of Science and Technology, Taipei, Taiwan (Po-Lun Chang) |
| Abstract | This paper proposes a robust validity index for Fuzzy c-Means (FCM) algorithm. The Fuzzy c-Means algorithm has become of most widely used method in fuzzy clustering. After clustering, it is often necessary to evaluate its results. Such assessment techniques are called cluster validity. The disadvantage of FCM is that the number of clusters must be predetermined. Even if the number of clusters is given, the clustering results of these algorithms are influenced by the choice of initial cluster centers. In this paper, a new cluster validity index is proposed to evaluate the fitness of clusters obtained by FCM. The example shows the result of proposed index have good performances than other cluster validities. |
| Starting Page | 767 |
| Ending Page | 771 |
| File Size | 661538 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424485017 |
| ISSN | 2157362X |
| e-ISBN | 9781424485031 |
| e-ISBN | 9781424485024 |
| DOI | 10.1109/IEEM.2010.5675607 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-12-07 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | clustering algorithm Noise Clustering algorithms Robustness Partitioning algorithms Indexes Mathematical model Validity index subtractive clustering algorithm Equations |
| Content Type | Text |
| Resource Type | Article |
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