Covers the five Vs of big data for a holistic understanding of modern data challenges
Discusses granular computing as a solution to complex learning tasks with large data
Reviews key traditional machine learning algorithms and their shortcomings in big data scenarios
Provides case studies using biomedical and sentiment data to illustrate granular computing applications
Explores theoretical, practical, and methodological impacts of granular computing in machine learning
Summarized by Shop
This book explores the significant role of granular computing in advancing machine learning towards in-depth processing of big data. It begins by introducing the main characteristics of big data, i.e., the five Vs—Volume, Velocity, Variety, Veracity and Variability. The book explores granular computing as a response to the fact that learn