Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner / Edition 1

Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner / Edition 1

by Galit Shmueli, Nitin R. Patel, Peter C. Bruce
     
 

In today's world, businesses are becoming more capable of accessing their ideal consumers, and an understanding of data mining contributes to this success. Data Mining for Business Intelligence, which was developed from a course taught at the Massachusetts Institute of Technology's Sloan School of Management, and the University of Maryland's Smith School of Business,… See more details below

Overview

In today's world, businesses are becoming more capable of accessing their ideal consumers, and an understanding of data mining contributes to this success. Data Mining for Business Intelligence, which was developed from a course taught at the Massachusetts Institute of Technology's Sloan School of Management, and the University of Maryland's Smith School of Business, uses real data and actual cases to illustrate the applicability of data mining intelligence to the development of successful business models. Featuring XLMiner[Registered], the Microsoft Office Excel[Registered] add-in, this book allows readers to follow along and implement algorithms at their own speed, with a minimal learning curve. In addition, students and practitioners of data mining techniques are presented with hands-on, business-oriented applications. An abundant amount of exercises and examples are provided to motivate learning and understanding.

Data Mining for Business Intelligence: Provides both a theoretical and practical understanding of the key methods of classification, prediction, reduction, exploration, and affinity analysis, Features a business decision-making context for these key methods, Illustrates the application and interpretation of these methods using real business cases and data. This book helps readers understand the beneficial relationship that can be established between data mining and smart business practices, and is an excellent learning tool for creating valuable strategies and making wiser business decisions.

About the Author:
Galit Shmueli, PhD, is Assistant Professor of Statistics in the Decision and Information Technologies Department of the Robert H. Smith School of Business at the University of Maryland

About the Author:
Nitin R. Patel, PhD, is Chairman, Founder, and Chief Technology Officer of Cambridge-based Cytel Incorporated and a Visiting Professor in the Engineering Systems Division at the Massachusetts Institute of Technology

Read More

Product Details

ISBN-13:
9780470084854
Publisher:
Wiley
Publication date:
12/11/2006
Edition description:
Older Edition
Pages:
298
Product dimensions:
7.32(w) x 10.12(h) x 0.79(d)

Table of Contents

Foreword.

Preface.

Acknowledgments.

1. Introduction.

2. Overview of the Data Mining Process.

3. Data Exploration and Dimension Reduction.

4. Evaluating Classification and Predictive Performance.

5. Multiple Linear Regression.

6. Three Simple Classification Methods.

7. Classification and Regression trees.

8. Logistic Regression.

9. Neural Nets.

10. Discriminant Analysis.

11. Association Rules.

12. Cluster Analysis.

13. Cases.

References.

Index.

Customer Reviews

Average Review:

Write a Review

and post it to your social network

     

Most Helpful Customer Reviews

See all customer reviews >