TY - GEN
T1 - Clustering based on density estimation with sparse grids
AU - Peherstorfer, Benjamin
AU - Pflüger, Dirk
AU - Bungartz, Hans Joachim
PY - 2012
Y1 - 2012
N2 - We present a density-based clustering method. The clusters are determined by splitting a similarity graph of the data into connected components. The splitting is accomplished by removing vertices of the graph at which an estimated density function of the data evaluates to values below a threshold. The density function is approximated on a sparse grid in order to make the method feasible in higher-dimensional settings and scalable in the number of data points. With benchmark examples we show that our method is competitive with other modern clustering methods. Furthermore, we consider a real-world example where we cluster nodes of a finite element model of a Chevrolet pick-up truck with respect to the displacements of the nodes during a frontal crash.
AB - We present a density-based clustering method. The clusters are determined by splitting a similarity graph of the data into connected components. The splitting is accomplished by removing vertices of the graph at which an estimated density function of the data evaluates to values below a threshold. The density function is approximated on a sparse grid in order to make the method feasible in higher-dimensional settings and scalable in the number of data points. With benchmark examples we show that our method is competitive with other modern clustering methods. Furthermore, we consider a real-world example where we cluster nodes of a finite element model of a Chevrolet pick-up truck with respect to the displacements of the nodes during a frontal crash.
KW - clustering
KW - density estimation
KW - sparse grids
UR - http://www.scopus.com/inward/record.url?scp=84868236159&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84868236159&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-33347-7_12
DO - 10.1007/978-3-642-33347-7_12
M3 - Conference contribution
AN - SCOPUS:84868236159
SN - 9783642333460
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 131
EP - 142
BT - KI 2012
T2 - 35th Annual German Conference on Artificial Intelligence, KI 2012
Y2 - 24 September 2012 through 27 September 2012
ER -