Evaluation of Subspace Clustering Using Internal Validity Measures

Evaluation of Subspace Clustering Using Internal Validity Measures

Different clustering algorithms, or even the same algorithm with different input parameters, can produce different data partitioning. Then, clustering validity measures are applied in order to determine which results have better quality than others. External measures can be used for evaluation of...

Full description

Bibliographic Details
Main Authors: OSZUST, M., KOSTKA, M.
Format: Article
Language:English
Published: Stefan cel Mare University of Suceava 2015-08-01
Series:Advances in Electrical and Computer Engineering
Subjects:
pattern recognition
data mining
subspace clustering
clustering validation
distance metrics
Online Access:http://dx.doi.org/10.4316/AECE.2015.03020

Internet

http://dx.doi.org/10.4316/AECE.2015.03020

Similar Items