Guide To Intelligent Data Analysis
User Manual:
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Page Count: 399 [warning: Documents this large are best viewed by clicking the View PDF Link!]
- Preface
- Contents
- Symbols
- Introduction
- Practical Data Analysis: An Example
- Project Understanding
- Data Understanding
- Principles of Modeling
- Data Preparation
- Finding Patterns
- Clustering
- Hierarchical Clustering
- Prototype-Based Clustering
- Density-Based Clustering
- Self-organizing Maps
- Association Rules
- Deviation Analysis
- Hierarchical Clustering
- Notion of (Dis-)Similarity
- Prototype- and Model-Based Clustering
- Density-Based Clustering
- Self-organizing Maps
- Frequent Pattern Mining and Association Rules
- Deviation Analysis
- Finding Patterns in Practice
- Further Reading
- References
- Finding Explanations
- Finding Predictors
- Evaluation and Deployment
- Appendix A Statistics
- Terms and Notation
- Descriptive Statistics
- Probability Theory
- Inferential Statistics
- Appendix B The R Project
- Appendix C KNIME
- References
- Index