Maximum certainty data partitioning.
Problems in data analysis often require the unsupervised partitioning of a dataset into clusters. Many methods exist for such partitioning but most have the weakness of being model-based (most assuming hyper-ellipsoidal clusters) or computationally infeasible in anything more than a three-dimensiona...
| Main Authors: | , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2000
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