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Book Categories |
Foreword | ||
Preface | ||
About the Editor | ||
Advisory Board | ||
Contributors | ||
I | Methodologies of Data Mining | |
1 | Decision Trees | 3 |
2 | Association Rules | 25 |
3 | Artificial Neural Network Models for Data Mining | 41 |
4 | Statistical Analysis of Normal and Abnormal Data | 67 |
5 | Bayesian Data Analysis | 103 |
6 | Hidden Markov Processes and Sequential Pattern Mining | 133 |
7 | Strategies and Methods for Prediction | 159 |
8 | Principal Components and Factor Analysis | 193 |
9 | Psychometric Methods of Latent Variable Modeling | 215 |
10 | Scalable Clustering | 247 |
11 | Time Series Similarities and Indexing | 279 |
12 | Nonlinear Time Series Analysis | 305 |
13 | Distributed Data Mining | 341 |
II | Management of Data Mining | |
14 | Data Collection, Preparation, Quality, and Visualization | 365 |
15 | Data Storage and Management | 393 |
16 | Feature Extraction, Selection, and Construction | 409 |
17 | Performance Analysis and Evaluation | 425 |
18 | Security and Privacy | 441 |
19 | Emerging Standards and Interfaces | 453 |
III | Applications of Data Mining | |
20 | Mining Human Performance Data | 463 |
21 | Mining Text Data | 481 |
22 | Mining Geospatial Data | 519 |
23 | Mining Science and Engineering Data | 549 |
24 | Mining Data in Bioinformatics | 573 |
25 | Mining Customer Relationship Management (CRM) Data | 597 |
26 | Mining Computer and Network Security Data | 617 |
27 | Mining Image Data | 637 |
28 | Mining Manufacturing Quality Data | 657 |
Author Index | 669 | |
Subject Index | 681 |
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