Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques
(2 Volumes)
Edited By:
Emilio Soria Olivas, University of Valencia, Spain;
José David Martín Guerrero, University of Valencia, Spain;
Marcelino Martinez-Sober, University of Valencia, Spain;
Jose Rafael Magdalena-Benedito, University of Valencia, Spain;
Antonio José Serrano-López, University of Valencia, Spain
Description:
The machine learning approach provides a useful tool when the amount of data is very large and a model is not available to explain the generation and relation of the data set.
The Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques provides a set of practical applications for solving problems and applying various techniques in automatic data extraction and setting. A defining collection of field advancements, this Handbook of Research fills the gap between theory and practice, providing a strong reference for academicians, researchers, and practitioners.
Key Features:
29 authoritative contributions by over 78 of the world’s leading expert in machine learning application from 15 countries
Comprehensive coverage of each specific topic, highlighting recent trends and describing the latest advances in the field
More than 1,414 references to existing literature and research on machine learning application
A compendium of over 244 key terms with detailed definitions
Organized by topic and indexed, making it a convenient method of reference for all IT/IS scholars and professionals
Cross-referencing of key terms, figures, and information pertinent to machine learning application
