| Status | 已發表Published |
| Fuzzy KNN Method With Adaptive Nearest Neighbors | |
Bian, Z.K.; Vong, C.M.; Wong, P.K.; Wang, S.T.
| |
| 2020-11-01 | |
| Source Publication | IEEE Transactions on Cybernetics (SCI-E) (Published online)
 |
| ISSN | 2168-2267 |
| Pages | 1-14 |
| Abstract | Due to its strong performance in handling uncertain and ambiguous data, the fuzzy k-nearest-neighbor method (FKNN) has realized substantial success in a wide variety of applications. However, its classification performance would be heavily deteriorated if the number k of nearest neighbors was unsuitably fixed for each testing sample. This study examines the feasibility of using only one fixed k value for FKNN on each testing sample. A novel FKNN-based classification method, namely, fuzzy KNN method with adaptive nearest neighbors (A-FKNN), is devised for learning a distinct optimal k value for each testing sample. In the training stage, after applying a sparse representation method on all training samples for reconstruction, A-FKNN learns the optimal k value for each training sample and builds a decision tree (namely, A-FKNN tree) from all training samples with new labels (the learned optimal k values instead of the original labels), in which each leaf node stores the corresponding optimal k value. In the testing stage, A-FKNN identifies the optimal k value for each testing sample by searching the A-FKNN tree and runs FKNN with the optimal k value for each testing sample. Moreover, a fast version of A-FKNN, namely, FA-FKNN, is designed by building the FA-FKNN decision tree, which stores the optimal k value with only a subset of training samples in each leaf node. Experimental results on 32 UCI datasets demonstrate that both A-FKNN and FA-FKNN outperform the compared methods in terms of classification accuracy, and FA-FKNN has a shorter running time. |
| Keyword | Decision tree fuzzy k-nearest-neighbor method (FKNN) nearest neighbors sparse representation/reconstruction |
| URL | View the original |
| Language | 英語English |
| The Source to Article | PB_Publication |
| PUB ID | 58823 |
| Document Type | Journal article |
| Collection | Faculty of Science and Technology |
| Corresponding Author | Wang, S.T. |
| Recommended Citation GB/T 7714 | Bian, Z.K.,Vong, C.M.,Wong, P.K.,et al. Fuzzy KNN Method With Adaptive Nearest Neighbors[J]. IEEE Transactions on Cybernetics (SCI-E) (Published online), 2020, 1-14. |
| APA | Bian, Z.K.., Vong, C.M.., Wong, P.K.., & Wang, S.T. (2020). Fuzzy KNN Method With Adaptive Nearest Neighbors. IEEE Transactions on Cybernetics (SCI-E) (Published online), 1-14. |
| MLA | Bian, Z.K.,et al."Fuzzy KNN Method With Adaptive Nearest Neighbors".IEEE Transactions on Cybernetics (SCI-E) (Published online) (2020):1-14. |
| Files in This Item: | There are no files associated with this item. | |||||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment