which clustering method is considered to be the best among DBSCAN and HDBSCAN and what is the reason behind that?
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The main disavantage of DBSCAN is that is much more prone to noise, which may lead to false clustering. On the other hand, HDBSCAN focus on high density clustering, which reduces this noise clustering problem and allows a hierarchical clustering based on a decision tree approach.
For a head to head comparison between DBSCAN and HDBSCAN: DBSCAN / HDBSCAN Clustering
For an explanation of many clustering methods until HDBSCAN you can check here: Comparing Python Clustering Algorithms

Eduardo Gomes
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