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Handbook of Statistical Analysis and Data Mining Applications (Nisbet)

 Author(s)  Robert Nisbet, John Elder, Gary Miner
 Title  Handbook of Statistical Analysis and Data Mining Applications
 Edition  1st
 Year  2009
 Publisher  Elsevier Inc.
 ISBN  978-0-12-374765-5
 book link 
 another book link 

Files and data associated with the tutorials may be found here.

Table of Contents

Forwards (Dean Abbott and Tony Lachenbruch)

PART I: History of Phases of Data Analysis, Basic Theory, and the Data Mining Process
Chapter 1. History - The Phases of Data Analysis throughout the Ages
Chapter 2. Theory
Chapter 3. The Data Mining Process
Chapter 4. Data Understanding and Preparation
Chapter 5. Feature Selection - Selecting the Best Variables
Chapter 6: Accessory Tools and Advanced Features in Data

PART II: - The Algorithms in Data Mining and Text Mining, and the Organization of the Three most common Data Mining Tools
Chapter 7. Basic Algorithms
Chapter 8: Advanced Algorithms
Chapter 9. Text Mining
Chapter 10. Organization of 3 Leading Data Mining Tools
Chapter 11. Classification Trees = Decision Trees
Chapter 12. Numerical Prediction (Neural Nets and GLM)
Chapter 13. Model Evaluation and Enhancement
Chapter 14. Medical Informatics
Chapter 15. Bioinformatics
Chapter 16. Customer Response Models
Chapter 17. Fraud Detection

PART III: Tutorials - Step-by-Step Case Studies as a Starting Point to learn how to do Data Mining Analyses

  • Listing of Guest Authors of the Tutorials
  • Tutorials within the book pages:
  • How to use the DMRecipe
  • Aviation Safety using DMRecipe
  • Movie Box-Office Hit Prediction using SPSS CLEMENTINE
  • Bank Financial data - using SAS-EM
  • Credit Scoring
  • CRM Retention using CLEMENTINE
  • Automobile - Cars - Text Mining
  • Quality Control using Data Mining
  • Three integrated tutorials from different domains, but all using C&RT to predict and display possible structural relationships among data:
  • Business Administration in a Medical Industry
  • Clinical Psychology- Finding Predictors of Correct Diagnosis
  • Education - Leadership Training: for Business and Education
  • Additional tutorials are available either on the accompanying CD-DVD, or the Elsevier Web site for this book
  • Listing of Tutorials on Accompanying CD

PART IV: Paradox of Complex Models; using the “right model for the right use”, on-going development, and the Future.
Chapter 18: Paradox of Ensembles and Complexity
Chapter 19: The Right Model for the Right Use
Chapter 20: The Top 10 Data Mining Mistakes
Chapter 21: Prospect for the Future - Developing Areas in Data Mining
Chapter 22: Summary



CD - With Additional Tutorials, data sets, Power Points, and Data Mining software (STATISTICA Data Miner & Text Miner & QC-Miner - 90 day free trial)

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