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Mandal / Dasgupta / Mukhopadhyay

Algorithms in Machine Learning Paradigms

Medium: Buch
ISBN: 978-981-15-1040-3
Verlag: Springer Nature Singapore
Erscheinungstermin: 04.01.2020
Lieferfrist: bis zu 10 Tage

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.



Produkteigenschaften


  • Artikelnummer: 9789811510403
  • Medium: Buch
  • ISBN: 978-981-15-1040-3
  • Verlag: Springer Nature Singapore
  • Erscheinungstermin: 04.01.2020
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2020
  • Serie: Studies in Computational Intelligence
  • Produktform: Gebunden
  • Gewicht: 483 g
  • Seiten: 195
  • Format (B x H x T): 160 x 241 x 17 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

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: ACombined 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.