Book description
Showing how data mining can improve the performance of organizations, this book and its R-based software provide the skills and tools needed to successfully develop advanced analytics capabilities. It explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems. The authors also give insight into some of the challenges faced when deploying these tools. Readers can access a powerful, GUI-enhanced customized R package online as well as example data sets on the book's website.
Table of contents
- Preliminaries
- Series
- Dedication
- Preface
-
Part I Purpose and Process
- Chapter 1 Database Marketing and Data Mining
- Chapter 2 A Process Model for Data Mining—CRISP-DM
-
Part II Predictive Modeling Tools
-
Chapter 3 Basic Tools for Understanding Data
- 3.1 Measurement Scales
- 3.2 Software Tools
- 3.3 Reading Data into R Tutorial
- 3.4 Creating Simple Summary Statistics Tutorial
- 3.5 Frequency Distributions and Histograms Tutorial
- 3.6 Contingency Tables Tutorial
-
- Figure 3.1
- Figure 3.2
- Figure 3.3
- Figure 3.4
- Figure 3.5
- Figure 3.6
- Figure 3.7
- Figure 3.8
- Figure 3.9
- Figure 3.10
- Figure 3.11
- Figure 3.12
- Figure 3.13
- Figure 3.14
- Figure 3.15
- Figure 3.16
- Figure 3.17
- Figure 3.18
- Figure 3.19
- Figure 3.20
- Figure 3.21
- Figure 3.22
- Figure 3.23
- Figure 3.24
- Figure 3.25
- Figure 3.26
- Figure 3.27
- Figure 3.28
- Figure 3.29
- Figure 3.30
- Figure 3.31
- Figure 3.32
- Figure 3.33
- Figure 3.34
- Figure 3.35
- Figure 3.36
- Figure 3.37
- Figure 3.38
- Figure 3.39
- Figure 3.40
- Figure 3.41
- Figure 3.42
- Figure 3.43
- Figure 3.44
- Figure 3.45
- Figure 3.46
- Figure 3.47
- Figure 3.48
- Figure 3.49
- Figure 3.50
- Figure 3.51
- Figure 3.52
- Chapter 4 Multiple Linear Regression
- Chapter 5 Logistic Regression
- Chapter 6 Lift Charts
- Chapter 7 Tree Models
- Chapter 8 Neural Network Models
-
Chapter 9 Putting It All Together
- 9.1 Stepwise Variable Selection
-
9.2 The Rapid Model Development Framework
- 9.2.1 Up-Selling Using the Wesbrook Database
- 9.2.2 Think about the Behavior That You Are Trying to Predict
- 9.2.3 Carefully Examine the Variables Contained in the Data Set
- 9.2.4 Use Decision Trees and Regression to Find the Important Predictor Variables
- 9.2.5 Use a Neural Network to Examine Whether Nonlinear Relationships Are Present
- 9.2.6 If There Are Nonlinear Relationships, Use Visualization to Find and Understand Them
- 9.3 Applying the Rapid Development Framework Tutorial
-
Chapter 3 Basic Tools for Understanding Data
-
Part III Grouping Methods
- Chapter 10 Ward's Method of Cluster Analysis and Principal Components
- Chapter 11 K-Centroids Partitioning Cluster Analysis
- Bibliography
Product information
- Title: Customer and Business Analytics
- Author(s):
- Release date: May 2012
- Publisher(s): Chapman and Hall/CRC
- ISBN: 9781498759700
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