Data Mining for the Social Sciences

PART 1. CONCEPTS 1. What Is Data Mining? 2. Contrasts with the Conventional Statistical Approach 3. Some General Strategies Used in Data Mining 4. Important Stages in a Data Mining Project PART 2. WORKED EXAMPLES 5. Preparing Training and Test Datasets 6. Variable Selection Tools 7. Creating New Variables Using Binning and Trees 8. Extracting Variables 9. Classifiers 10. Classification Trees 11. Neural Networks 12. Clustering 13. Latent Class Analysis and Mixture Models 14. Association Rules Conclusion Bibliography Notes Index