Answer / Prashant Dhillo

DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is a clustering algorithm required for several reasons. First, it can effectively identify clusters of varying densities without the need to specify the number of clusters in advance. This makes DBSCAN particularly useful when the number or shape of the clusters is unknown. Additionally, DBSCAN is capable of handling noisy data and separating noise points from true clusters. Lastly, DBSCAN is robust against outliers, as it does not assume a specific distribution for the data.

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