MulSim: A Novel Similar-to-Multiple-Point Clustering Algorithm
Finding clusters in datasets with different distributions and sizes is challenging when clusters are of widely various shapes, sizes, and densities. Based on a similar-to-multiple-point clustering strategy, a novel and simple clustering algorithm named MulSim is presented to address these issues in...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2018-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8572688/ |