Assessing and quantifying clusteredness: The OPTICS Cordillera
Data representations in low dimensions such as results from unsupervised dimensionality reduction methods are often visually interpreted to find clusters of observations. To identify clusters the result must be appreciably clustered. This property of a result may be called "clusteredness"....
| Main Authors: | , , |
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| Format: | Others |
| Language: | en |
| Published: |
WU Vienna University of Economics and Business
2016
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| Subjects: | |
| Online Access: | http://epub.wu.ac.at/4789/1/opticscordillera.pdf |