A general probabilistic framework for clustering individuals and objects

This paper presents a unifying probabilisti framework for lustering individuals or systems into groups when the available data measurements are not multivariate ve tors of xed dimensionality and shows that a number of earlier algorithms an be viewed as spe ial ases within this unifying framework.

Abstract

Article Free Access Share on A general probabilistic framework for clustering individuals and objects Authors: Igor V. Cadez Department of Information and Computer Science, University of California, Irvine, Irvine, CA Department of Information and Computer Science, University of California, Irvine, Irvine, CAView Profile , Scott Gaffney Department of Information and Computer Science, University of California, Irvine, Irvine, CA Department of Information and Computer Science, University of California, Irvine, Irvine, CAView Profile , Padhraic Smyth Department of Information and Computer Science, University of California, Irvine, Irvine, CA Department of Information and Computer Science, University of California, Irvine, Irvine, CAView Profile Authors Info & Claims KDD '00: Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data miningAugust 2000 Pages 140–149https://doi.org/10.1145/347090.347119Online:01 August 2000Publication History 99citation913DownloadsMetricsTotal Citations99Total Downloads913Last 12 Months19Last 6 weeks3 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF