High Density Subspace Clustering Algorithm for High Dimensional Data
Highdimensional data have the characteristics of sparsity and vulnerability to dimension disaster, which makes it is difficult to ensure the precision and efficiency of high dimensional data clustering Therefore the method of subspace clustering is adopted to reduce the impact of sparsity and dimens...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Harbin University of Science and Technology Publications
2020-08-01
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| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1909 |
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