Understanding DBSCAN Clustering The DBSCAN clustering algorithm is probably best understood by walking through a concrete example. Assume that epsilon = 1.5 and minPoints = 2, as in the demo. The ...

Self-organizing maps can be used for several purposes other than clustering. A standard, non-clustering SOM usually creates a square matrix, such as 4-by-4, called the map. For a clustering SOM, even ...