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Clustering is an interdisciplinary-studied subject of statistical data analysis. In this study, among various types of clustering algorithms, the algorithms derived from Density Based Spatial Clustering of Applications with Noise (DBSCAN) are investigated. Although DBSCAN is the well-known density-based algorithms it has some bottlenecks. So, enhanced versions of DBSCAN are developed to provide some...
Clustering is the problem of finding relations in a data set in an supervised manner. These relations can be extracted using the density of a data set, where density of a data point is defined as the number of data points around it. To find the number of data points around another point, region queries are adopted. Region queries are the most expensive construct in density based algorithm, so it should...
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