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Machine Learning for Intelligent Decision Science

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Machine Learning for Intelligent Decision Science/ edited by Jitendra Kumar Rout, Minakhi Rout, Himansu Das.
other author:	Rout, Jitendra Kumar.
Description:	XII, 209 p. 113 illus., 78 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computational intelligence. -
Online resource:	https://doi.org/10.1007/978-981-15-3689-2
ISBN:	9789811536892

Machine Learning for Intelligent Decision Science
Machine Learning for Intelligent Decision Science[electronic resource] /edited by Jitendra Kumar Rout, Minakhi Rout, Himansu Das. - 1st ed. 2020. - XII, 209 p. 113 illus., 78 illus. in color.online resource. - Algorithms for Intelligent Systems,2524-7565. - Algorithms for Intelligent Systems,.

Development of Different Machine Learning Ensemble Classifier for Gully Erosion Susceptibility in Gandheswari Watershed of West Bengal, India -- Classification of ECG Heartbeat using Deep Convolutional Neural Network -- Breast Cancer Identification and Diagnosis Techniques -- Energy Efficient Resource Allocation in Data Centers using a Hybrid Evolutionary Algorithm -- Root Cause Analysis using Ensemble Model for Intelligent Decision-Making -- Spider Monkey Optimization Algorithm in Data Science: A Quantifiable Objective Study -- Multi-Agent Based Systems In Machine Learning and Its Practical Case Studies -- Computer Vision and Machine Learning Approach for Malaria Diagnosis in Thin Blood Smears from Microscopic Blood Images. .

The book discusses machine learning-based decision-making models, and presents intelligent, hybrid and adaptive methods and tools for solving complex learning and decision-making problems under conditions of uncertainty. Featuring contributions from data scientists, practitioners and educators, the book covers a range of topics relating to intelligent systems for decision science, and examines recent innovations, trends, and practical challenges in the field. The book is a valuable resource for academics, students, researchers and professionals wanting to gain insights into decision-making.

ISBN: 9789811536892

Standard No.: 10.1007/978-981-15-3689-2doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Machine Learning for Intelligent Decision Science
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520 $a The book discusses machine learning-based decision-making models, and presents intelligent, hybrid and adaptive methods and tools for solving complex learning and decision-making problems under conditions of uncertainty. Featuring contributions from data scientists, practitioners and educators, the book covers a range of topics relating to intelligent systems for decision science, and examines recent innovations, trends, and practical challenges in the field. The book is a valuable resource for academics, students, researchers and professionals wanting to gain insights into decision-making.
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