Uncertainty Modeling for Data Mining: A Label Semantics Approach

Outlining a new research direction in fuzzy set theory applied to data mining, this volume proposes a number of new data mining algorithms and includes dozens of figures and illustrations that help the reader grasp the complexities of the concepts. Read More

Outlining a new research direction in fuzzy set theory applied to data mining, this volume proposes a number of new data mining algorithms and includes dozens of figures and illustrations that help the reader grasp the complexities of the concepts. Read Less

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  	This is a digital edition of this title. Rent eBook (5 Options) 30 Day Rental: $29.70 (Expires Jul 31, 2024) 60 Day Rental: $39.60 (Expires Aug 30, 2024) 90 Day Rental: $49.50 (Expires Sep 29, 2024) 120 Day Rental: $59.40 (Expires Oct 29, 2024) 180 Day Rental: $64.35 (Expires Dec 28, 2024) Buy eBook Lifetime Access: $99.00 Title: Uncertainty Modeling for Data Mining by Zengchang Qin; Yongchuan Tang Publisher: Springer Nature Print ISBN: 9783642412509, 3642412505 eText ISBN: 9783642412516 Edition: 2014 2014 edition Format: PDF eBook	$29.70 Rent eBook This is a digital eBook Nothing will be shipped to you Works with web browsers and the VitalSource app on all Windows, Mac, Chromebook, Kindle Fire, iOS, and Android devices Most eBooks are returnable within 14 days of purchase Questions? See our eBook FAQ