Hand D., Mannila H., Smyth P. Principles Of Data Mining

Cambridge: The MIT Press, 2001. — 546 p. — ISBN: 026208290X.The rapid growth and integration of databases provides scientists, engineers, and business people with a vast new resource that can be analyzed to make scientific discoveries, optimize industrial systems, and uncover financially valuable patterns. To undertake these large data analysis projects, researchers and practitioners have adopted established algorithms from statistics, machine learning, neural networks, and databases and have also developed new methods targeted at large data mining problems. Principles of Data Mining by David Hand, Heikki Mannila, and Padhraic Smyth provides practioners and students with an introduction to the wide range of algorithms and methodologies in this exciting area. The interdisciplinary nature of the field is matched by these three authors, whose expertise spans statistics, databases, and computer science. The result is a book that not only provides the technical details and the mathematical principles underlying data mining methods, but also provides a valuable perspective on the entire enterprise.Principles of Data MiningMeasurement and Data
Visualizing and Exploring Data
Data Analysis and Uncertainty
A Systematic Overview of Data Mining Algorithms
Models and Patterns
Score Functions for Data Mining Algorithms
Search and Optimization Methods
Descriptive Modeling
Predictive Modeling for Classification
Predictive Modeling for Regression
Data Organization and Databases
Finding Patterns and Rules
Retrieval by Content
Appendix - Random VariablesList of Examples
Principles