Algorithms in Machine Learning Paradigms / edited by Jyotsna Kumar Mandal, Somnath Mukhopadhyay, Paramartha Dutta, Kousik Dasgupta.

• 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. . 

Ämnesord

Applied mathematics.  (LCSH)

Engineering mathematics.  (LCSH)

Machine learning.  (LCSH)

Optical data processing.  (LCSH)

Natural language processing (Computer science).  (LCSH)

Signal processing.  (LCSH)

Image processing.  (LCSH)

Speech processing systems.  (LCSH)

Mathematical and Computational Engineering. 

Machine Learning. 

Image Processing and Computer Vision. 

Natural Language Processing (NLP). 

Signal, Image and Speech Processing. 

Klassifikation

TA329-348 (LCC)

TA640-643 (LCC)

TEC009000 (ämneskategori)

TBJ (ämneskategori)

519 (DDC)

Tal (kssb/8 (machine generated))