Handbook of Statistical Analysis and Data Mining Applications,

Edition 1

Editors: By John Elder, IV; Edited by Robert Nisbet and Gary Miner

Publication Date: 22 May 2009

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The Handbook of Statistical Analysis and Data Mining Applications is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers (both academic and industrial) through all stages of data analysis, model building and implementation. The Handbook helps one discern the technical and business problem, understand the strengths and weaknesses of modern data mining algorithms, and employ the right statistical methods for practical application. Use this book to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques, and discusses their application to real problems, in ways accessible and beneficial to practitioners across industries - from science and engineering, to medicine, academia and commerce. This handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build successful data mining solutions.

Key Features

Written "By Practitioners for Practitioners"
Non-technical explanations build understanding without jargon and equations
Tutorials in numerous fields of study provide step-by-step instruction on how to use supplied tools to build models
Practical advice from successful real-world implementations
Includes extensive case studies, examples, MS PowerPoint slides and datasets
CD-DVD with valuable fully-working 90-day software included: "Complete Data Miner - QC-Miner - Text Miner" bound with book

About the author

By John Elder, IV, Elder Research, Inc. and the University of Virginia, Charlottesville, USA; Edited by Robert Nisbet, University of California, Irvine Predictive Analytics Certification Program, and at the University of California, Santa Barbara and Gary Miner, StatSoft, Inc., Tulsa, OK, USA

PART I: History of Phases of Data Analysis, Basic Theory, and the Data Mining Process
1. History – The Phases of Data Analysis throughout the Ages
2. Theory
3. The Data Mining Process
4. Data Understanding and Preparation
5. Feature Selection – Selecting the Best Variables
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
7. Basic Algorithms
8: Advanced Algorithms
9. Text Mining
10. Organization of 3 Leading Data Mining Tools
11. Classification Trees = Decision Trees
12. Numerical Prediction (Neural Nets and GLM)
13. Model Evaluation and Enhancement
14. Medical Informatics
15. Bioinformatics
16. Customer Response Models
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.
18: Paradox of Ensembles and Complexity
19: The Right Model for the Right Use
20: The Top 10 Data Mining Mistakes
21: Prospect for the Future – Developing Areas in Data Mining
22: Summary

GLOSSARY of STATISICAL and DATA MINING TERMS
INDEX
CD – With Additional Tutorials, data sets, Power Points, and Data Mining software (STATISTICA Data Miner & Text Miner & QC-Miner – 90 day free trial)

ISBN: 9780123747655

Page Count: 864

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Handbook of Statistical Analysis and Data Mining Applications,

Editors: By John Elder, IV; Edited by Robert Nisbet and Gary Miner

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