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Rough set-based classification systems

Author: Robert K Nowicki
Publisher: Cham, Switzerland : Springer, [2019]
Series: Studies in computational intelligence, v. 802.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This book demonstrates an original concept for implementing the rough set theory in the construction of decision-making systems. It addresses three types of decisions, including those in which the information or input data is insufficient. Though decision-making and classification in cases with missing or inaccurate data is a common task, classical decision-making systems are not naturally adapted to it. One  Read more...
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Details

Genre/Form: Electronic books
Additional Physical Format: (OCoLC)1056741980
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Robert K Nowicki
ISBN: 9783030038953 3030038955
OCLC Number: 1080644917
Description: 1 online resource.
Contents: Introduction --
Rough Set Theory Fundamentals --
Rough Fuzzy Classification Systems --
Fuzzy Rough Classification Systems --
Rough Neural Network Classifier --
Rough Nearest Neighbour Classifier --
Ensembles of Rough Set–Based Classifiers --
Final Remarks.
Series Title: Studies in computational intelligence, v. 802.
Responsibility: Robert K. Nowicki.

Abstract:

Pawlak.The proposed classifiers are applied and tested in two configurations: The first is an iterative mode in which a single classification system requests completion of the input data until an  Read more...

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