Title :
A simple linear time (1 + ϵ)-approximation algorithm for k-means clustering in any dimensions
Author :
Kumar, Amit ; Sabharwal, Yogish ; Sen, Sandeep
Author_Institution :
Dept. of Comput. Sci. & Engg., IIT Delhi, New Delhi, India
Abstract :
We present the first linear time (1 + ε)-approximation algorithm for the k-means problem for fixed k and ε. Our algorithm runs in O(nd) time, which is linear in the size of the input. Another feature of our algorithm is its simplicity - the only technique involved is random sampling.
Keywords :
approximation theory; computational complexity; pattern clustering; random processes; sampling methods; k-means clustering; linear time approximation algorithm; random sampling; Application software; Clustering algorithms; Computer science; Data mining; Image processing; Image retrieval; Image sampling; Information retrieval; Partitioning algorithms; Web search;
Conference_Titel :
Foundations of Computer Science, 2004. Proceedings. 45th Annual IEEE Symposium on
Print_ISBN :
0-7695-2228-9
DOI :
10.1109/FOCS.2004.7
