Statistical and Machine-Learning Data Mining

Two Basic Data Mining Methods for Variable Assessment. CHAID-based Data Mining for Paired-Variable Assessment. The Importance of Straight Data. Symmetrizing Ranked Data. Principal Component Analysis. The Correlation Coefficient. Logistic Regression. Ordinary Regression. Variable Selection Methods in Regression. CHAID for Interpreting a Logistic Regression Model. The Importance of the Regression Coefficient.The Average Correlation. CHAID for Specifying a Model with Interaction Variables. Market-segmentation Classification Modeling with Logistic Regression. CHAID as a Method for Filling in Missing Values. Identifying Your Best Customers. Assessment of Marketing Models. Bootstrapping in Marketing. Validating the Logistic Regression Model. Visualization of Marketing Models. The Predictive Contribution Coefficient. Regression Modeling Involves Art, Science, and Poetry Too. Genetic and Statistic Regression Models. A Data Mining Method for Moderating Outliers, Instead of Discarding Them. Overfitting. The Importance of Straight Data. The GenIQ Model. Finding the Best Variables for Marketing Models. Interpretation of Coefficient-Free Models.