Laser & Optoelectronics Progress, Volume. 58, Issue 8, 0810006-1(2021)
Weighted FCM Clustering Algorithm Based on Jeffrey Divergence Similarity Measure
Fig. 1. Convergence analysis of four clustering algorithms. (a) FCM; (b) K-means; (c) DPC; (d) JW-FCM
Fig. 2. Clustering results of four clustering algorithms on Spiral data set. (a) FCM; (b) K-means; (c) DPC; (d) JW-FCM
Fig. 3. Clustering results of four clustering algorithms on S1 data set. (a) FCM; (b) K-means; (c) DPC; (d) JW-FCM
Fig. 4. Clustering results of four clustering algorithms on ISquare2 data set. (a) FCM; (b) K-means; (c) DPC; (d) JW-FCM
Fig. 5. Comparison of ACC indicators
Fig. 6. Comparison of ARI indicators
Fig. 7. Robustness comparison on Wine data set
Fig. 8. Robustness comparison on Thyroid data set
Fig. 9. Robustness comparison on D31 data set
Fig. 10. Robustness comparison on S1 data set
Fig. 11. Robustness comparison on Isquare2 data set
Fig. 12. Robustness comparison on Spiral data set
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Chenwen Wu, Ning Ma, Yufan Jiang. Weighted FCM Clustering Algorithm Based on Jeffrey Divergence Similarity Measure[J]. Laser & Optoelectronics Progress, 2021, 58(8): 0810006-1
Category: Image Processing
Received: Jul. 13, 2020
Accepted: Sep. 9, 2020
Published Online: Apr. 6, 2021
The Author Email: Ma Ning (2996771799@qq.com)