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arXiv · 1809.06189

ADBSCAN: Adaptive Density-Based Spatial Clustering of Applications with Noise for Identifying Clusters with Varying Densities

Mohammad Mahmudur Rahman Khan·Md. Abu Bakr Siddique·Rezoana Bente Arif·Mahjabin Rahman Oishe
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Abstract

Density-based spatial clustering of applications with noise (DBSCAN) is a data clustering algorithm which has the high-performance rate for dataset where clusters have the constant density of data points. One of the significant attributes of this algorithm is noise cancellation. However, DBSCAN demonstrates reduced performances for clusters with different densities. Therefore, in this paper, an adaptive DBSCAN is proposed which can work significantly well for identifying clusters with varying densities.

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Mohammad Mahmudur Rahman Khan, Md. Abu Bakr Siddique, Rezoana Bente Arif, Mahjabin Rahman Oishe. 2018-09-17. ADBSCAN: Adaptive Density-Based Spatial Clustering of Applications with Noise for Identifying Clusters with Varying Densities. https://doi.org/10.1109/ceeict.2018.8628138

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