Machine Learning Paradigms: Theory and Application
- Length: 483 pages
- Edition: 1
- Language: English
- Publisher: Springer
- Publication Date: 2018-12-21
- ISBN-10: 3030023567
- ISBN-13: 9783030023560
- Sales Rank: #7698318 (See Top 100 Books)
The book focuses on machine learning. Divided into three parts, the first part discusses the feature selection problem. The second part then describes the application of machine learning in the classification problem, while the third part presents an overview of real-world applications of swarm-based optimization algorithms.
The concept of machine learning (ML) is not new in the field of computing. However, due to the ever-changing nature of requirements in today’s world it has emerged in the form of completely new avatars. Now everyone is talking about ML-based solution strategies for a given problem set. The book includes research articles and expository papers on the theory and algorithms of machine learning and bio-inspiring optimization, as well as papers on numerical experiments and real-world applications.
Cover Front Matter Part I. Machine Learning in Feature Selection Hybrid Feature Selection Method Based on the Genetic Algorithm and Pearson Correlation Coefficient Weighting Attributes and Decision Rules Through Rankings and Discretisation Parameters Greedy Selection of Attributes to Be Discretised Part II. Machine Learning in Classification and Ontology Machine Learning for Enhancement Land Cover and Crop Types Classification An Optimal Machine Learning Classification Model for Flash Memory Bit Error Prediction Comparative Analysis of the Fault Diagnosis in CHMLI Using k-NN Classifier Based on Different Feature Extractions Design and Development of an Intelligent Ontology-Based Solution for Energy Management in the Home Towards a Personalized Learning Experience Using Reinforcement Learning Towards Objective-Dependent Performance Analysis on Online Sentiment Review Enhancing Performance of Hybrid Named Entity Recognition for Amazighe Language A Real-Time Aspect-Based Sentiment Analysis System of YouTube Cooking Recipes Detection of Palm Tree Pests Using Thermal Imaging: A Review Unleashing Machine Learning onto Big Data: Issues, Challenges and Trends Part III. Bio-inspiring Optimization and Applications Bio-inspired Based Task Scheduling in Cloud Computing Parameters Optimization of Support Vector Machine Based on the Optimal Foraging Theory Solving Constrained Non-linear Integer and Mixed-Integer Global Optimization Problems Using Enhanced Directed Differential Evolution Algorithm Optimizing Support Vector Machine Parameters Using Bat Optimization Algorithm Performance Evaluation of Sine-Cosine Optimization Versus Particle Swarm Optimization for Global Sequence Alignment Problem BCLO—Brainstorming and Collaborative Learning Optimization Algorithms PID Controller Tuning Parameters Using Meta-heuristics Algorithms: Comparative Analysis Real-Parameter Unconstrained Optimization Based on Enhanced AGDE Algorithm Bio-inspired Optimization Algorithms for Segmentation and Removal of Interphase Cells from Metaphase Chromosomes Images
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