Year: 2013
Type: preprint
Abstract: We develop the heuristic PROBI for the probabilistic Euclidean k-median problem based on a coreset construction by Lammersen et al. Our algorithm computes a summary of the data and then uses an adapted version of k-means++ (Arthur and Vassilvitskii, 2007) to compute a good solution on the summary. The summary is maintained in a data stream, so PROBI can be used in a data stream setting on very large data sets. We experimentally evaluate the quality of the summary and of the computed solution and compare the running time to state of the art data stream clustering algorithms.
Source: arXiv (Cornell University)
Authors: Fichtenberger, Hendrik, Schmidt, Melanie
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2406823964