# Introduction After mastering the centroid-based clustering and hierarchical clustering methods, we also need to learn the density-based clustering method. Density-based clustering divides the corresponding categories by evaluating the densities of the samples. In theory, it is possible to find clusters of any shape and effectively avoid noise interference. In addition, density-based clustering is the same as hierarchical clustering, with no need to declare the number of categories in advance.
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