From Building Better Models with JMP Pro. Full book available for purchase here.

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From Building Better Models with JMP Pro. Full book available for purchase here. Contents Acknowledgments... ix About This Book... xi About These Authors... xiii Part 1 Introduction.

1 From Building Better Models with JMP Pro. Full book available for purchase here. Contents Acknowledgments... ix About This Book... xi About These Authors... xiii Part 1 Introduction... 1 Chapter 1 Introduction... 3 Overview... 3 Analytics Is Hot!... 4 What You Will Learn... 6 Analytics and Data Mining... 7 How the Book Is Organized... 7 Let s Get Started... 8 References... 9 Chapter 2 An Overview of the Business Analytics Process Introduction Commonly Used Process Models The Business Analytics Process Define the Problem Prepare for Modeling Modeling Deploy Model Monitor Performance Conclusion References... 17

2 iv Part 2 Model Building Chapter 3 Working with Data Introduction JMP Basics Opening JMP and Getting Started JMP Data Tables Examining and Understanding Your Data Preparing Data for Modeling Summary and Getting Help in JMP Exercises References Part 3 Model Selection and Advanced Methods Chapter 4 Multiple Linear Regression In the News Representative Business Problems Preview of End Result Looking Inside the Black Box: How the Algorithm Works Example 1: Housing Prices Applying the Business Analytics Process Summary Example 2: Bank Revenues Applying the Business Analytics Process Summary Exercises References Chapter 5 Logistic Regression In the News Representative Business Problems Preview of the End Result Looking Inside the Black Box: How the Algorithm Works Example 1: Lost Sales Opportunities Applying the Business Analytics Process

3 v Example 2: Titanic Passengers Applying the Business Analytics Process Summary Key Take-Aways and Additional Considerations Exercises References Chapter 6 Decision Trees In the News Representative Business Problems Preview of the End Result Looking Inside the Black Box: How the Algorithm Works Classification Tree for Status Statistical Details Behind Classification Trees Other General Modeling Considerations Exploratory Modeling versus Predictive Modeling Model Cross-Validation Dealing with Missing Values Decision Tree Modeling with Ordinal Predictors Example 1: Credit Card Marketing The Study Applying the Business Analytics Process Case Summary Example 2: Printing Press Yield The Study Applying the Business Analytics Process Case Summary Summary Exercises References Chapter 7 Neural Networks In the News Representative Business Problems Measuring Success Preview of the End Result

4 vi Looking Inside the Black Box: How the Algorithm Works Neural Networks with Categorical Responses Example 1: Churn Applying the Business Analytics Process Modeling The Neural Model and Results Case Summary Example 2: Credit Risk Applying the Business Analytics Process Case Summary Summary and Key Take-Aways Exercises References Part 4 Model Selection and Advanced Methods Chapter 8 Using Cross-Validation Overview Why Cross-Validation? Partitioning Data for Cross-Validation Using a Random Validation Portion Specifying the Validation Roles for Each Row K-fold Cross-Validation Using Cross-Validation for Model Fitting in JMP Pro Example Creating Training, Validation, and Test Subsets Examining the Validation Subsets Using Cross-Validation to Build a Linear Regression Model Choosing the Regression Model Terms with Stepwise Regression Making Predictions Using Cross-Validation to Build a Decision Tree Model Fitting a Neural Network Model Using Cross-Validation Model Comparison Key Take-Aways Exercises References

5 vii Chapter 9 Advanced Methods Overview Concepts in Advanced Modeling Bagging Boosting Regularization Advanced Partition Methods Bootstrap Forest Boosted Tree Boosted Neural Network Models Generalized Regression Models Maximum Likelihood Regression Ridge Regression Lasso Regression Elastic Net Key Take-Aways Exercises References Chapter 10 Capstone and New Case Studies Introduction Case Study 1: Cell Classification Stage 1: Define the Problem Stage 2: Prepare for Modeling Stage 3: Modeling Case Study 2: Blue Book for Bulldozers (Kaggle Contest) Getting to Know the Data Data Preparation Modeling Model Comparison Next Steps Case Study 3: Default Credit Card, Presenting Results to Management Developing a Management Report Case Study 4: Carvana (Kaggle Contest) Exercises References

Preface to the Second Edition. Preface to the First Edition. 1 Introduction 1

Preface to the Second Edition. Preface to the First Edition. 1 Introduction 1 Preface to the Second Edition Preface to the First Edition vii xi 1 Introduction 1 2 Overview of Supervised Learning 9 2.1 Introduction... 9 2.2 Variable Types and Terminology... 9 2.3 Two Simple Approaches