Algorithms in Machine Learning Paradigms

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.

Dr. Jyotsna Kumar Mandal is a Professor of Computer Science & Engineering, and former Dean of FETM, Kalyani University, India. He holds an M.Sc. in Physics from Jadavpur University, M. Tech. in Computer Science from the University of Calcutta, and was awarded a Ph.D. in Computer Science & Engineering by Jadavpur University. He has 32 years of teaching and research experience in various fields of computer science and allied areas, and has published 170 articles in journals, more than 300 articles at conferences, and edited 31 volumes and seven books. He is a Fellow of IETE, life member of CRSI and CSI, and senior member of IEEE.