Data Mining
About this book
This book on data mining explores a broad set of ideas and presents some of the state-of-the-art research in this field. The book is triggered by pervasive applications that retrieve knowledge from real-world big data. Data mining finds applications in the entire spectrum of science and technology including basic sciences to life sciences and medicine, to social, economic, and cognitive sciences, to engineering and computers. The chapters discuss various applications and research frontiers in data mining with algorithms and implementation details for use in real-world. This can be through characterization, classification, discrimination, anomaly detection, association, clustering, trend or evolution prediction, etc. The intended audience of this book will mainly consist of researchers, research students, practitioners, data analysts, and business professionals who seek information on the various data mining techniques and their applications.
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Information
Table of contents
- Data Mining
- Contents
- Preface
- Chapter 1 Ensemble Methods in Environmental Data Mining
- Chapter 2 Estimating Customer Lifetime Value Using Machine Learning Techniques
- Chapter 3 Determination and Classification of Crew Productivity with Data Mining Methods
- Chapter 4 Mining HCI Data for Theory of Mind Induction
- Chapter 5 Performance-Aware High-Performance Computing for Remote Sensing Big Data Analytics
- Chapter 6 Early Prediction of Patient Mortality Based on Routine Laboratory Tests and Predictive Models in Critically Ill Patients
- Chapter 7 Semantic Infrastructure for Service Environment Supporting Successful Aging
- Chapter 8 Adaptive Neural Network Classifier-Based Analysis of Big Data in Health Care
- Chapter 9 Identification of Research Thematic Approaches Based on Keywords Network Analysis in Colombian Social Sciences
- Chapter 10 Data Privacy for Big Data Publishing Using Newly Enhanced PASS Data Mining Mechanism