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Machine learning for intelligent dec...

Das, Himansu.

Machine learning for intelligent decision science

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning for intelligent decision scienceedited by Jitendra Kumar Rout, Minakhi Rout, Himansu Das.
other author:	Rout, Jitendra Kumar.
Published:	Singapore :Springer Singapore :2020.
Description:	xii, 209 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Machine learning.
Online resource:	https://doi.org/10.1007/978-981-15-3689-2
ISBN:	9789811536892$q(electronic bk.)

Machine learning for intelligent decision science
Machine learning for intelligent decision science[electronic resource] /edited by Jitendra Kumar Rout, Minakhi Rout, Himansu Das. - Singapore :Springer Singapore :2020. - xii, 209 p. :ill., digital ;24 cm. - 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$q(electronic bk.)

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

188639
Machine learning.

LC Class. No.: Q325.5 / .M334 2020

Dewey Class. No.: 006.31

Machine learning for intelligent decision science
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245 0 0 $a Machine learning for intelligent decision science $h [electronic resource] / $c edited by Jitendra Kumar Rout, Minakhi Rout, Himansu Das.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2020.
300 $a xii, 209 p. : $b ill., digital ; $c 24 cm.
490 1 $a Algorithms for intelligent systems, $x 2524-7565
505 0 $a 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.
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.
650 0 $a Machine learning. $3 188639
650 1 4 $a Computational Intelligence. $3 338479
650 2 4 $a Machine Learning. $3 833608
650 2 4 $a Data Engineering. $3 839346
650 2 4 $a Data Mining and Knowledge Discovery. $3 275288
700 1 $a Rout, Jitendra Kumar. $3 859869
700 1 $a Rout, Minakhi. $3 859870
700 1 $a Das, Himansu. $3 837884
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Algorithms for intelligent systems. $3 857955
856 4 0 $u https://doi.org/10.1007/978-981-15-3689-2
950 $a Intelligent Technologies and Robotics (Springer-42732)