1. Enhancing Model Performance 

2. A Variable Selection Method that Provides a Unique Ranking of Variable Importance

3. CHAID for Uncovering Relationships: A Data Mining Tool

4. The GenIQ Model: When Data Are Not Straight 

5. Assessing the Importance of Variables in Database Response Models

6 .Expanding Your Statistical Computing Toolbox

7. Building a Database Zipcode Acquisition Model

8. When Data Are Too Large to Handle in the Memory of Your Computer

9. Data Preparation for Determining Sample Size 

10. Data Preparation for Big Data

11. Response-Approval Model: An Effective Approach for Implemenation 

12. Modeling a Distribution with a Mass at Zero

13. A New Method of Modeling Missing Data: Deliverance of Discarded, Incomplete Cases

14. Calculating Complete-case Analysis Sample Size  

15. A Genetic Jackknife Method: 3-in-1 Tool for Variable Selection, Data Mining and Model Building

16. A Regression Tree Approach for Optimizing Price and Package Offerings

17. A Better Method for Building a High-value Customer Model

18. A Model-free Approach to Conjoint Analysis for Optimizing Price and Package Offerings

19. A Simple Bootstrap Variable Selection Method for Building Database Marketing Models

20. Determining Which Variables in a Model Are Its Most Important Predictors: The Predictive Contribution Coefficient

21. "How Large a Sample is Required to Build a Database Response Model?"

22. A Hybrid Statistics-Machine Learning Paradigm for Database Response Modeling 

23. Building a CRM Model for Identifying Profitable Leads: The Genetic Contact-Profit Model

24. A New Technique for B-to-B Lead Generation: The Genetic Contact-Conversion Model

25. A New CRM Method for Generating Successful Leads: The Genetic Contact-Conversion Model

26. Data Mining for Predictive Value of Discarded Individuals with Missing Data

27. A Non-Imputation Methodology for Database Modeling with Missing Data

28. The Working Concepts for Building a Database Acquisition Model

29. The Working Concepts for Building a Database Retention Model

30. The Working Concepts for Building a Database Attrition Model

31. A Simple Method for Assessing Linear Trend and Seasonality Components in Database Models

32. Handling Qualitative Attributes: Upgrading Discrete Heritable Information

33. The Banking Industry Problem-Solution: Reduce Costs, Increase Profits by Data Mining and Modeling