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Applied Intelligent Decision Making In Machine Learning Himansu Das Editor

  • SKU: BELL-22130062
Applied Intelligent Decision Making In Machine Learning Himansu Das Editor
$ 31.00 $ 45.00 (-31%)

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Applied Intelligent Decision Making In Machine Learning Himansu Das Editor instant download after payment.

Publisher: CRC Press
File Extension: PDF
File size: 35.09 MB
Pages: 262
Author: Himansu Das (editor), Jitendra Kumar Rout (editor), Suresh Chandra Moharana (editor), Nilanjan Dey (editor)
ISBN: 9780367503369, 9781003049548, 0367503360, 1003049540
Language: English
Year: 2021

Product desciption

Applied Intelligent Decision Making In Machine Learning Himansu Das Editor by Himansu Das (editor), Jitendra Kumar Rout (editor), Suresh Chandra Moharana (editor), Nilanjan Dey (editor) 9780367503369, 9781003049548, 0367503360, 1003049540 instant download after payment.

The objective of this edited book is to share the outcomes from various research domains to develop efficient, adaptive, and intelligent models to handle the challenges related to decision making. 

It incorporates the advances in 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 systems, forecasting air quality, healthcare, exchange rate prediction, and image dehazing. It also provides a premier interdisciplinary platform for scientists, researchers, practitioners, and educators to share their thoughts in the context of recent innovations, trends, developments, practical challenges, and advancements in the field of data mining, machine learning, soft computing, and decision science. It also focuses on the usefulness of applied intelligent techniques in the decision-making process in several aspects.

To address these objectives, this edited book includes a dozen chapters contributed by authors from around the globe. The authors attempt to solve these complex problems using several intelligent machine-learning techniques. This allows researchers to understand the mechanism needed to harness the decision-making process using machine-learning techniques for their own respective endeavors.

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