Generalizing Local Density for Density-Based Clustering
نویسندگان
چکیده
Discovering densely-populated regions in a dataset of data points is an essential task for density-based clustering. To do so, it often necessary to calculate each point’s local density the dataset. Various definitions have been proposed literature. These can be divided into two categories: Radius-based and k Nearest Neighbors-based. In this study, we find commonality between these types propose canonical form density. With form, pros cons existing better explored, new derived investigated.
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ژورنال
عنوان ژورنال: Symmetry
سال: 2021
ISSN: ['0865-4824', '2226-1877']
DOI: https://doi.org/10.3390/sym13020185