of University Florida
CISE department
Gator Engineering
Clustering
Part 4
Dr. Sanjay Ranka Professor Computer and Information Science and Engineering University of Florida, Gainesville
University of Florida
CISE department
Gator Engineering
DBSCAN
DBSCAN is a density based clustering algorithm Density = number of points within a specified radius (Eps) A point is a core point if it has more than specified number of points (MinPts) within Eps
Core point is in the interior of a cluster
A border point has fewer than MinPts within Eps but is in neighborhood of a core point A noise point is any point that is neither a core point nor a border point
Data Mining Sanjay Ranka Fall 2003 2
1
University of Florida
CISE department
Gator Engineering
DBSCAN: Core, Border and Noise points
Data Mining
Sanjay Ranka
Fall 2003
3
University of Florida
CISE department
Gator Engineering
When DBSCAN works well
Original Dataset
Clusters found by DBSCAN
Data Mining
Sanjay Ranka
Fall 2003
4
2
University of Florida
CISE department
Gator Engineering
DBSCAN: Core, Border and Noise points
Original Points
Eps = 10, Minpts = 4 Point types: Core Border Noise
Fall 2003 5
Data Mining
Sanjay Ranka
University of Florida
CISE department
Gator Engineering
DBSCAN: Determining Eps and MinPts
Idea is that for points in a cluster, there kth nearest neighbors are at roughly the same distance Noise points have the kth nearest neighbor at at farther distance So, plot sorted distance of every point to its kth nearest neighbor. (k=4 used for...
dm5part4-color