Data Mining for Business Intelligence

Learn how to develop models for classification, prediction, and customer segmentation with the help of Data Mining for Business Intelligence In today's world, businesses are becoming more capable of accessing their ideal consumers, and an understanding of data mining contributes to this success.

List 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.

Product details

• Authors: Peter C. Bruce, et al, Nitin R. Patel, Galit Shmueli
• Publisher: Wiley, John and Sons Ltd
• Languages: English
• Product format: Hardback
• Released: 02.01.2007
• EAN: 9780470084854
• ISBN: 978-0-470-08485-4
• No. of pages: 298
• Dimensions: 82 mm x 2601 mm x 18 mm
• Subject: Education and learning > Teaching preparation > Vocational needs