Density-Based Multiscale Analysis for Clustering in Strong Noise Settings With Varying Densities
نویسندگان
چکیده
منابع مشابه
Density-Based Multiscale Analysis for Clustering in Strong Noise Settings
Finding clustering patterns in data is challenging when clusters can be of arbitrary shapes and the data contains high percentage (e.g., 80%) of noise. This paper presents a novel technique named density-based multiscale analysis for clustering (DBMAC) that can conduct noise-robust clustering without any strict assumption on the shapes of clusters. Firstly, DBMAC calculates the r-neighborhood s...
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2018
ISSN: 2169-3536
DOI: 10.1109/access.2018.2836389