1. Chapter 13 Genetic Algorithms

2. 2 Data Mining Techniques So Far… Chapter 5 – Statistics Chapter 6 – Decision Trees Chapter 7 – Neural Networks Chapter 8 – Nearest Neighbor Approaches: Memory- Based Reasoning and Collaborative Filtering Chapter 9 – Market Basket Analysis & Association Rules Chapter 10 – Link Analysis Chapter 11 – Automatic Cluster Detection

3. 3 Genetic Algorithms Based on an analogy to biological processes – similar to neural networks and memory-based reasoning techniques Goal is to maximize the “fitness” Are being utilized for –Complex scheduling –Resource optimization –Classification Often used in tandem with other DM techniques Not too many DM software products support

4. 4 Genetic Algorithms Optimization problems involve “goodness of fit” or “fitness” –Example: A company produces widgets in a set of factories. Each factory has a capacity, a cost of production, and a cost for transporting widgets to customers. How many widgets should each factory produce to satisfy customer demand at minimal cost?

5. 5 End of Chapter 13