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Algorithms in machine learning paradigms

Mandal, Jyotsna Kumar.

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Algorithms in machine learning paradigms

Record Type:	Electronic resources : Monograph/item
Title/Author:	Algorithms in machine learning paradigms/ edited by Jyotsna Kumar Mandal ... [et al.].
other author:	Mandal, Jyotsna Kumar.
Published:	Singapore :Springer Singapore : : 2020.,
Description:	x, 195 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Chapter 1. Development of Trapezoidal Hesitant-Intuitionistic Fuzzy Prioritized Operators based on Einstein Operations with their Application to Multi-Criteria Group Decision Making -- Chapter 2. Graph-based Information-Theoretic Approach for Unsupervised Feature Selection -- Chapter 3. Fact based Expert System for supplier selection with ERP data -- Chapter 4. Handling Seasonal Pattern and Prediction using Fuzzy Time Series Model -- Chapter 5. Automatic Classification of Fruits and Vegetables: A Texture-based Approach -- Chapter 6. Deep Learning based Early Sign Detection Model for Proliferative Diabetic Retinopathy in Neovascularization at the Disc -- Chapter 7. A Linear Regression Based Resource Utilization Prediction Policy For Live Migration in Cloud Computing -- Chapter 8. Tracking changing human emotions from facial image sequence by landmark triangulation: A incircle-circumcircle duo approach -- Chapter 9. Recognizing Human Emotions from Facial Images by Landmark Triangulation: A Combined Circumcenter-Incenter-Centroid Trio Feature Based Method -- Chapter 10. Stable neighbor nodes prediction with multivariate analysis in mobile ad hoc network using RNN model -- Chapter 11. A New Approach for Optimizing Initial Parameters of Lorenz Attractor and its application in PRNG.
Contained By:	Springer Nature eBook
Subject:	Machine learning. -
Online resource:	https://doi.org/10.1007/978-981-15-1041-0
ISBN:	9789811510410

Algorithms in machine learning paradigms
Algorithms in machine learning paradigms[electronic resource] /edited by Jyotsna Kumar Mandal ... [et al.]. - Singapore :Springer Singapore :2020. - x, 195 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.8701860-949X ;. - Studies in computational intelligence ;v.870..

Chapter 1. Development of Trapezoidal Hesitant-Intuitionistic Fuzzy Prioritized Operators based on Einstein Operations with their Application to Multi-Criteria Group Decision Making -- Chapter 2. Graph-based Information-Theoretic Approach for Unsupervised Feature Selection -- Chapter 3. Fact based Expert System for supplier selection with ERP data -- Chapter 4. Handling Seasonal Pattern and Prediction using Fuzzy Time Series Model -- Chapter 5. Automatic Classification of Fruits and Vegetables: A Texture-based Approach -- Chapter 6. Deep Learning based Early Sign Detection Model for Proliferative Diabetic Retinopathy in Neovascularization at the Disc -- Chapter 7. A Linear Regression Based Resource Utilization Prediction Policy For Live Migration in Cloud Computing -- Chapter 8. Tracking changing human emotions from facial image sequence by landmark triangulation: A incircle-circumcircle duo approach -- Chapter 9. Recognizing Human Emotions from Facial Images by Landmark Triangulation: A Combined Circumcenter-Incenter-Centroid Trio Feature Based Method -- Chapter 10. Stable neighbor nodes prediction with multivariate analysis in mobile ad hoc network using RNN model -- Chapter 11. A New Approach for Optimizing Initial Parameters of Lorenz Attractor and its application in PRNG.

This book presents studies involving algorithms in the machine learning paradigms. It discusses a variety of learning problems with diverse applications, including prediction, concept learning, explanation-based learning, case-based (exemplar-based) learning, statistical rule-based learning, feature extraction-based learning, optimization-based learning, quantum-inspired learning, multi-criteria-based learning and hybrid intelligence-based learning.

ISBN: 9789811510410

Standard No.: 10.1007/978-981-15-1041-0doiSubjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5 / .A54 2020

Dewey Class. No.: 006.31

Algorithms in machine learning paradigms
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245 0 0 $a Algorithms in machine learning paradigms $h [electronic resource] / $c edited by Jyotsna Kumar Mandal ... [et al.].
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2020.
300 $a x, 195 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v v.870
505 0 $a Chapter 1. Development of Trapezoidal Hesitant-Intuitionistic Fuzzy Prioritized Operators based on Einstein Operations with their Application to Multi-Criteria Group Decision Making -- Chapter 2. Graph-based Information-Theoretic Approach for Unsupervised Feature Selection -- Chapter 3. Fact based Expert System for supplier selection with ERP data -- Chapter 4. Handling Seasonal Pattern and Prediction using Fuzzy Time Series Model -- Chapter 5. Automatic Classification of Fruits and Vegetables: A Texture-based Approach -- Chapter 6. Deep Learning based Early Sign Detection Model for Proliferative Diabetic Retinopathy in Neovascularization at the Disc -- Chapter 7. A Linear Regression Based Resource Utilization Prediction Policy For Live Migration in Cloud Computing -- Chapter 8. Tracking changing human emotions from facial image sequence by landmark triangulation: A incircle-circumcircle duo approach -- Chapter 9. Recognizing Human Emotions from Facial Images by Landmark Triangulation: A Combined Circumcenter-Incenter-Centroid Trio Feature Based Method -- Chapter 10. Stable neighbor nodes prediction with multivariate analysis in mobile ad hoc network using RNN model -- Chapter 11. A New Approach for Optimizing Initial Parameters of Lorenz Attractor and its application in PRNG.
520 $a This book presents studies involving algorithms in the machine learning paradigms. It discusses a variety of learning problems with diverse applications, including prediction, concept learning, explanation-based learning, case-based (exemplar-based) learning, statistical rule-based learning, feature extraction-based learning, optimization-based learning, quantum-inspired learning, multi-criteria-based learning and hybrid intelligence-based learning.
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650 0 $a Computer algorithms. $3 523872
650 1 4 $a Mathematical and Computational Engineering. $3 3226306
650 2 4 $a Machine Learning. $3 3382522
650 2 4 $a Image Processing and Computer Vision. $3 891070
650 2 4 $a Natural Language Processing (NLP) $3 3381674
650 2 4 $a Signal, Image and Speech Processing. $3 891073
700 1 $a Mandal, Jyotsna Kumar. $3 3218496
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