Machine Learning Paradigms: Theory and Application

Machine Learning Paradigms: Theory and Application (Studies in Computational Intelligence)
ISBN-10 书号: 3030023567
ISBN-13 书号: 9783030023560
Edition 版本: 1st ed. 2019
Release Finelybook 出版日期: 2018-12-08
pages 页数: (474 )

$179.99


Book Description to Finelybook sorting

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.

Partl. 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 ll. 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 You Tube Cooking Recipes
Detection of Palm Tree Pests Using Thermal lmaging:A Review
Unleashing Machine Learning onto Big Data: Ilssues, Challenges and Trends
Part ll. 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 lmages

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