Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science. Big Data Analytics for Sustainable Computing is a collection of innovative rese.

• Title Page
• Copyright Page
• Book Series
• Editorial Advisory Board
• Table of Contents
• Detailed Table of Contents
• Preface
• Acknowledgment
• Chapter 1: Understanding Big Data
• Chapter 2: A Detailed Study on Classification Algorithms in Big Data
• Chapter 3: Big Data and Analytics
• Chapter 4: Decoding Big Data Analytics for Emerging Business Through Data-Intensive Applications and Business Intelligence
• Chapter 5: Feature Selection Algorithm Using Relative Odds for Data Mining Classification
• Chapter 6: Social Network Analysis
• Chapter 7: Role of Machine Intelligence and Big Data in Remote Sensing
• Chapter 8: Provisioning System for Application Virtualization Environments
• Chapter 9: Big Data-Based Spectrum Sensing for Cognitive Radio Networks Using Artificial Intelligence
• Chapter 10: Big Data Analytics in the Healthcare Industry
• Chapter 11: Big Data Analytics and Visualization for Food Health Status Determination Using Bigmart Data
• Chapter 12: “Saksham Model” Performance Improvisation Using Node Capability Evaluation in Apache Hadoop
• Compilation of References
• About the Contributors
• Index