The book consists of three sections. The first,foundations, provides a tutorial overview of theprinciples underlying data mining algorithms and theirapplication. The presentation emphasizes intuitionrather than rigor. The second section, data miningalgorithms, shows how algorithms are constructed tosolve specific problems in a principled manner. Thealgorithms covered include trees and rules.
目 錄
Full Contents
List of Tables
List of Figures
Series Foreword
Preface
1 Introduction
2 Measurement and Data
3 Visualizing and Exploring Data
4 Data Analysis and Uncertainty
5 A Systematic Overview of Data Mining Algorithms
6 Models and Patterns
7 Score Functions for Data Mining Algorithms
8 Search and Optimization Methods
9 Descriptive Modeling
10 Predictive Modeling for Classification
11 Predictive Modeling for Regression
12 Data Organization and Databases
13 Finding Patterns and Rule
14 Retrieval by Content
Appendix: Random Variables
References
Index
