Python Machine Learning - Second Edition

Locating regions of high density via DBSCAN

Although we can't cover the vast amount of different clustering algorithms in this chapter, let's at least introduce one more approach to clustering: Density-based Spatial Clustering of Applications with Noise (DBSCAN), which does not make assumptions about spherical clusters like k-means, nor does it partition the dataset into hierarchies that require a manual cut-off point. As its name implies, density-based clustering assigns cluster labels based on dense regions of points. In DBSCAN, the notion of density is defined as the number of points within a specified radius .

According to the DBSCAN algorithm, ...