Author(s) Name:  Bruce Ratner

About the Book:

   Interest in predictive analytics of big data has grown exponentially in the four years since the publication of Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition.
   In the third edition of this bestseller, the author has completely revised, reorganized, and repositioned the original chapters and produced 13 new chapters of creative and useful machine-learning data mining techniques. In sum, the 43 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature.

Table of Contents

  1. Introduction
  2. Science Dealing with Data: Statistics and Data Science
  3. Two Basic Data Mining Methods for Variable Assessment
  4. CHAID-Based Data Mining for Paired-Variable Assessment
  5. The Importance of Straight Data Simplicity and Desirability for Good Model-Building Practice
  6. Symmetrizing Ranked Data: A Statistical Data Mining Method for Improving the Predictive Power of Data
  7. Principal Component Analysis: A Statistical Data Mining Method for Many-Variable Assessment
  8. Market Share Estimation: Data Mining for an Exceptional Case
  9. The Correlation Coefficient: Its Values Range between Plus and Minus 1, or Do They?
  10. Logistic Regression: The Workhorse of Response Modeling
  11. Predicting Share of Wallet without Survey Data
  12. Ordinary Regression: The Workhorse of Profit Modeling
  13. Variable Selection Methods in Regression: Ignorable Problem, Notable Solution
  14. CHAID for Interpreting a Logistic Regression Model
  15. The Importance of the Regression Coefficien
  16. The Average Correlation: A Statistical Data Mining Measure for Assessment of Competing Predictive Models and the Importance of the Predictor Variables
  17. CHAID for Specifying a Model with Interaction Variables
  18. Market Segmentation Classification Modeling with Logistic Regression
  19. Market Segmentation Based on Time-Series Data Using Latent Class Analysis
  20. Market Segmentation: An Easy Way to Understand the Segments
  21. The Statistical Regression Model: An Easy Way to Understand the Model
  22. CHAID as a Method for Filling in Missing Values
  23. Model Building with Big Complete and Incomplete Data
  24. Art, Science, Numbers, and Poetry
  25. Identifying Your Best Customers: Descriptive, Predictive, and Look-Alike Profiling

ISBN:  9780367573607

Publisher:  Chapman and Hall/CRC Publisher

Year of Publication:  2017

Book Link:  Home Page Url