| 3.1 | Models and Patterns | ||
| 3.2 | Performance Measures | ||
| 3.3 | Forms of Knowledge | ||
| 3.4 | Induction from Data | ||
| 3.5 | Example of a Bad Classifier | ||
| 3.6 | Classification Techniques | ||
|
3.6.1 |
Decision Trees | ||
| 3.6.1.1 | Growing Decision Trees | ||
| 3.6.1.2 | Pruning Decision Trees | ||
| 3.6.1.3 | Rules from Decision Trees | ||
| 3.6.1.4 | Variants of Decision Trees | ||
| 3.6.2 | Linear Regression | ||
| 3.6.3 | Neural Networks | ||
| 3.6.4 | k-Nearest Neighbors | ||
| 3.6.5 | Naïve Bayesian Classifiers | ||
| 3.6.6 | Support Vectors Machines | ||
| 3.6.7 | Ensemble Methods | ||
| 3.7 | Handling Large Sized Data | ||
| 3.8 | |||
| 3.9 | Chapter Review Exercises | ||