Selective Nearest Neighbors Clustering

Article Type

Research Article

Publication Title

Pattern Recognition Letters

Abstract

In this paper, we propose a simple data clustering technique that uses the idea of creating a graph on the data points based on nearest neighbors and identifying clusters by finding connected components of the graph thus constructed. The algorithm forms the graph based on a border detection and an outlier detection technique. We also propose a novel outlier detection technique that is suitable for our implementation. We compare our method against state-of-the-art clustering techniques and perform experiments to analyze the effects of various aspects of a dataset on the proposed scheme.

First Page

178

Last Page

185

DOI

10.1016/j.patrec.2021.10.005

Publication Date

3-1-2022

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