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Item Details
Title: COMBINATORIAL DATA ANALYSIS
OPTIMIZATION BY DYNAMIC PROGRAMMING
By: Lawrence J. Hubert, Phipps Arabie, Jacqueline Meulman
Format: Hardback

List price: £48.99


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ISBN 10: 0898714788
ISBN 13: 9780898714784
Publisher: SOCIETY FOR INDUSTRIAL & APPLIED MATHEMATICS,U.S.
Pub. date: 1 January, 1987
Series: SIAM Monographs on Discrete Mathematics & Applications No. 6
Pages: 174
Description: Providea a comprehensive and self-contained review delineating a very general DP paradigm or schema that can serve two functions. First, the paradigm can be applied in various special forms to encompass all previously proposed applications suggested in the classification literature. Second, the paradigm can lead directly to many more novel uses.
Synopsis: Combinatorial data analysis (CDA) refers to a wide class of methods for the study of relevant data sets in which the arrangement of a collection of objects is absolutely central. The focus of this monograph is on the identification of arrangements, which are then further restricted to where the combinatorial search is carried out by a recursive optimization process based on the general principles of dynamic programming (DP). The authors provide a comprehensive and self-contained review delineating a very general DP paradigm or schema that can serve two functions. First, the paradigm can be applied in various special forms to encompass all previously proposed applications suggested in the classification literature. Second, the paradigm can lead directly to many more novel uses. An appendix is included as a user's manual for a collection of programs available as freeware. The incorporation of a wide variety of CDA tasks under one common optimization framework based on DP is one of the book's strongest points. The authors include verifiably optimal solutions to nontrivially sized problems over the array of data analysis tasks discussed.
Publication: US
Imprint: Society for Industrial & Applied Mathematics,U.S.
Returns: Returnable
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