Can I read Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling on EtoBox?

Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling by Ratner, Bruce; is a book available to read on EtoBox.

What is Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling about?

Front Cover 1 Dedication 6 Contents 8 Preface 20 Acknowledgments 24 About the Author 26 1. Introduction 28 2. Two Basic Data Mining Methods for Variable Assessment 44 3. CHAID-Based Data Mining for Paired-Variable Assessment 58 4. The Importance of Straight Data: Simplicity and Desirability for Good Model-Building Practice 72 5. Symmetrizing Ranked Data: A Statistical Data Mining Method for Improving the Predictive Power of Data 82 6. Principal Component Analysis: A Statistical Data Mining Method for Many-Variable Assessment 100 7. The Correlation Coefficient: Its Values Range between Plus/Minus 1, or Do They? 116 8. Logistic Regression: The Workhorse of Response Modeling 124 9. Ordinary Regression: The Workhorse of Profit Modeling 180 10. Variable Selection Methods in Regression: Ignorable Problem, Notable Solution 204 11. CHAID for Interpreting a Logistic Regression Model 222 12. The Importance of the Regression Coefficient 240 13. The Average Correlation: A Statistical Data Mining Measure for Assessment of Competing Predictive Models and the Importance of the Predictor Variables 252 14. CHAID for Specifying a Model with Interaction Variables 264 15. Market Segmentation Classific

Author

Ratner, Bruce;

Language

EN