Kernel Subspace Possibilistic Fuzzy C-Means Algorithm Driven by Feature Weights
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-4546-5_23
Reference17 articles.
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4. Frigui, H., Nasraoui, O.: Unsupervised learning of prototypes and attribute weights. Pattern Recogn. 37(3), 567–581 (2004)
5. Deng, Z., Choi, K.S., Chung, F.L., et al.: Enhanced soft subspace clustering integrating within-cluster and between-cluster information. Pattern Recogn. 43(3), 767–781 (2010)
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