Density-Based Spatial Clustering of Applications with Noise
Find clusters and outliers by using the DBSCAN algorithm
DBSCAN uses a density-based approach to find arbitrarily
shaped clusters and outliers (noise) in data. This technique is useful when you
do not know the number of clusters in advance. Use the
dbscan function to perform clustering on an input data matrix or
on pairwise distances between observations.
|Density-based spatial clustering of applications with noise (DBSCAN)|
Group data into clusters and identify outliers by using a density-based approach.