國立虎尾科技大學 |

Algorithms in Machine Learning Paradigms

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Algorithms in Machine Learning Paradigms/ edited by Jyotsna Kumar Mandal, Somnath Mukhopadhyay, Paramartha Dutta, Kousik Dasgupta.
其他作者:	Dasgupta, Kousik.
面頁冊數:	X, 195 p. 115 illus., 69 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Signal, Image and Speech Processing. -
電子資源:	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, Somnath Mukhopadhyay, Paramartha Dutta, Kousik Dasgupta. - 1st ed. 2020. - X, 195 p. 115 illus., 69 illus. in color.online resource. - Studies in Computational Intelligence,8701860-949X ;. - Studies in Computational Intelligence,564.

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:

670837
Signal, Image and Speech Processing.

LC Class. No.: TA329-348

Dewey Class. No.: 519

Algorithms in Machine Learning Paradigms
LDR:03225nam a22004215i 4500 001 1021802
003 DE-He213
005 20200702215948.0
007 cr nn 008mamaa
008 210318s2020 si | s |||| 0|eng d
020 $a 9789811510410 $9 978-981-15-1041-0
024 7 $a 10.1007/978-981-15-1041-0 $2 doi
035 $a 978-981-15-1041-0
050 4 $a TA329-348
050 4 $a TA640-643
072 7 $a TBJ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a TBJ $2 thema
082 0 4 $a 519 $2 23
245 1 0 $a Algorithms in Machine Learning Paradigms $h [electronic resource] / $c edited by Jyotsna Kumar Mandal, Somnath Mukhopadhyay, Paramartha Dutta, Kousik Dasgupta.
250 $a 1st ed. 2020.
264 1 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2020.
300 $a X, 195 p. 115 illus., 69 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Studies in Computational Intelligence, $x 1860-949X ; $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. .
650 2 4 $a Signal, Image and Speech Processing. $3 670837
650 2 4 $a Natural Language Processing (NLP). $3 1254293
650 2 4 $a Image Processing and Computer Vision. $3 670819
650 2 4 $a Machine Learning. $3 1137723
650 1 4 $a Mathematical and Computational Engineering. $3 1139415
650 0 $a Speech processing systems. $3 564428
650 0 $a Image processing. $3 557495
650 0 $a Signal processing. $3 561459
650 0 $a Natural language processing (Computer science). $3 802180
650 0 $a Optical data processing. $3 639187
650 0 $a Machine learning. $3 561253
650 0 $a Engineering mathematics. $3 562757
650 0 $a Applied mathematics. $3 1069907
700 1 $a Dasgupta, Kousik. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1281256
700 1 $a Dutta, Paramartha. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1048724
700 1 $a Mukhopadhyay, Somnath. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1171776
700 1 $a Mandal, Jyotsna Kumar. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1208238
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9789811510403
776 0 8 $i Printed edition: $z 9789811510427
776 0 8 $i Printed edition: $z 9789811510434
830 0 $a Studies in Computational Intelligence, $x 1860-949X ; $v 564 $3 1253640
856 4 0 $u https://doi.org/10.1007/978-981-15-1041-0
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)