2005

Data Mining and Knowledge Discovery Handbook

Editors:

ISBN: 978-0-387-24435-8 (Print) 978-0-387-25465-4 (Online)

Table of contents (68 chapters)

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  1. Introduction to Knowledge Discovery in Databases

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      Pages 1-17

      Introduction to Knowledge Discovery in Databases

  2. Preprocessing Methods

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      Pages 21-36

      Data Cleansing

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      Pages 37-57

      Handling Missing Attribute Values

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      Book Chapter

      Pages 59-91

      Geometric Methods for Feature Extraction and Dimensional Reduction

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      Pages 93-111

      Dimension Reduction and Feature Selection

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      Book Chapter

      Pages 113-130

      Discretization Methods

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      Book Chapter

      Pages 131-146

      Outlier Detection

  3. Supervised Methods

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      Pages 149-164

      Introduction to Supervised Methods

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      Book Chapter

      Pages 165-192

      Decision Trees

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      Book Chapter

      Pages 193-230

      Bayesian Networks

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      Book Chapter

      Pages 231-255

      Data Mining within a Regression Framework

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      Book Chapter

      Pages 257-276

      Support Vector Machines

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      Book Chapter

      Pages 277-294

      Rule Induction

  4. Unsupervised Methods

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      Book Chapter

      Pages 297-319

      Visualization and Data Mining for High Dimensional Datasets

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      Book Chapter

      Pages 321-352

      Clustering Methods

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      Book Chapter

      Pages 353-376

      Association Rules

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      Book Chapter

      Pages 377-397

      Frequent Set Mining

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      Book Chapter

      Pages 399-416

      Constraint-Based Data Mining

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      Book Chapter

      Pages 417-432

      Link Analysis

  5. Soft Computing Methods

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      Book Chapter

      Pages 435-467

      Evolutionary Algorithms for Data Mining

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