[SPT17] An Elliptical-Shaped Density-based Classification Algorithm for Detection of Entangled Clusters
Conférence Internationale avec comité de lecture :
25th European Signal Processing Conference (Eusipco 2017),
August 2017,
pp.1-5,
Kos ,
Greece,
Mots clés: clustering, density-based, ellipsoidal structures
Résumé:
We present a density-based clustering method producing
a covering of the dataset by ellipsoidal structures in
order to detect possibly entangled clusters. We first introduce an
unconstrained version of the algorithm which does not require
any assumption on the number of clusters. Then a constrained
version using a priori knowledge to improve the bare clustering
is discussed. We evaluate the performance of our algorithm
and several other well-known clustering methods using existing
cluster validity techniques on randomly-generated bi-dimensional
gaussian mixtures. Our simulation results show that both versions
of our algorithm compare well with the reference algorithms
according to the used metrics, foreseeing future improvements
of our method and further comparisons with other clustering
techniques.