Applied intelligent decision making in machine learning / Himansu Das, Jitendra Kumar Rout, Suresh Chandra Moharana, Nilanjan Dey.

Contributor(s):

Material type: Text

TextSeries: Computational intelligence in engineering problem solvingPublisher: Boca Raton : CRC Press, 2020Edition: 1Description: pages cmContent type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9780367503369

DDC classification:

006.31 APP

Other classification:

Summary: "The objective of this edited book is to share the outcomes on various research domains to develop efficient, adaptive, and intelligent models to handle the challenges related to decision making. It incorporates the advances of machine intelligent techniques such as data streaming, classification, clustering, pattern matching, feature selection, and deep learning in the decision-making process for several diversified applications such as agriculture, character recognition, landslide susceptibility, recommendation system, forecasting air quality, healthcare, exchange rate prediction, and image dehazing"-- Provided by publisher.

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Holdings
Item type	Current library	Home library	Call number	Status	Date due	Barcode
Book	Campus Library Kariavattom Processing Center	Campus Library Kariavattom	006.31 APP (Browse shelf(Opens below))	Available		UCL31768

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Previous	006.3 SHU.M Materials Design using computational intelligence techniques	006.30153 TUL.I Issues in artificial intelligence and cognitive science	006.303 KLO.H Handbook of data mining and knowledge discovery	006.31 APP Applied intelligent decision making in machine learning /	006.31 KNO.M Machine learning : a concise introduction /	006.31 SUG.D Density ratio estimation in machine learning	006.312 BEL.M Machine learning for big data: Hands-on for developers and technical professionals	Next

"The objective of this edited book is to share the outcomes on various research domains to develop efficient, adaptive, and intelligent models to handle the challenges related to decision making. It incorporates the advances of machine intelligent techniques such as data streaming, classification, clustering, pattern matching, feature selection, and deep learning in the decision-making process for several diversified applications such as agriculture, character recognition, landslide susceptibility, recommendation system, forecasting air quality, healthcare, exchange rate prediction, and image dehazing"-- Provided by publisher.

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