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OverviewData uncertainty is a concept closely related with most real life applications that involve data collection and interpretation. Examples can be found in data acquired with biomedical instruments or other experimental techniques. Integration of robust optimization in the existing data mining techniques aim to create new algorithms resilient to error and noise.This work encapsulates all the latest applications of robust optimization in data mining. This brief contains an overview of the rapidly growing field ofrobust data mining research field and presents the most well known machine learning algorithms, their robust counterpart formulations and algorithms for attacking these problems. Thisbrief will appeal to theoreticians and data miners working in this field. Full Product DetailsAuthor: Petros Xanthopoulos , Theodore B TrafalisPublisher: Springer New York Imprint: Springer New York ISBN: 9781283909174ISBN 10: 1283909170 Pages: 67 Publication Date: 01 January 2013 Audience: General/trade , General Format: Electronic book text Publisher's Status: Active Availability: Available To Order We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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