Ask
Search
Ask Question
Login
×
×
Welcome back.
and 2 others joined a min ago.
Continue with Google
Continue with email
0
11k
views
Write a short note on DBSCAN.
written
8.7 years ago
by
aartisahitya
•
160
modified 4.8 years ago by
prashantsaini
•
0
data warehouse and mining
ADD COMMENT
FOLLOW
SHARE
EDIT
1 Answer
0
659
views
written
8.7 years ago
by
aartisahitya
•
160
DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is a density based clustering algorithm.
The algorithm groups regions with sufficiently high density into clusters and discovers clusters of arbitrary shape in spatial databases with noise.
It defines a cluster as a maximal set of density-connected points.
Density = number of points within a specified radius (Eps)
A point is a core point if it has more than specified number of points (Min Pts) within Eps
Core point is in the interior of a cluster
A border point has fewer than Min Pts 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.
ADD COMMENT
SHARE
EDIT
Please
log in
to add an answer.
Community
Users
Levels
Badges
Content
All posts
Tags
Dashboard
Company
About
Team
Privacy
Submit question paper solutions and earn money