An approximation polynomial-time algorithm for a cardinality-weighted 2-clustering problem

We consider the strongly NP-hard problem of partitioning a set of Euclidean points into two clusters so as to minimize the sum over both clusters of the weighted sums of the squared intracluster distances from the elements of the clusters to their centers. The weights of sums are the cardinalities o...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	2017 International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON) s. 94 - 96
Hlavní autoři:	Kel'manov, Alexander, Motkova, Anna
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	IEEE 01.09.2017
Témata:	2-approximation polynomial-time algorithm Algorithm design and analysis Approximation algorithms Clustering algorithms Euclidean space Machine learning algorithms NP-hardness Partitioning algorithms Pattern recognition Weighted-clustering
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Popis
Shrnutí:	We consider the strongly NP-hard problem of partitioning a set of Euclidean points into two clusters so as to minimize the sum over both clusters of the weighted sums of the squared intracluster distances from the elements of the clusters to their centers. The weights of sums are the cardinalities of the clusters. The center of one of the clusters is given as input, while the center of the other cluster is unknown and determined as the average value over all points in the cluster. The variant of the problem in which the cardinalities of the clusters are parts of the input is analyzed. We present and prove a 2-approximation polynomial-time algorithm for this problem.
DOI:	10.1109/SIBIRCON.2017.8109845