book

Building Better Models with JMP Pro

Name: Building Better Models with JMP Pro
ISBN: 9781629599564

by Jim Grayson, Sam Gardner, Mia Stephens

August 2015

Beginner to intermediate

352 pages

7h 20m

English

SAS Institute

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Acknowledgments
About This Book
About These Authors
Part 1 Introduction
Chapter 1 Introduction
OverviewAnalytics Is Hot!What You Will LearnAnalytics and Data MiningHow the Book Is OrganizedLet’s Get StartedReferences
Chapter 2 An Overview of the Business Analytics Process
IntroductionCommonly Used Process ModelsThe Business Analytics ProcessDefine the ProblemPrepare for ModelingModelingDeploy ModelMonitor PerformanceConclusionReferences
Part 2 Preparing for Modeling
Chapter 3 Working with Data
IntroductionJMP BasicsOpening JMP and Getting StartedJMP Data TablesExamining and Understanding Your DataPreparing Data for ModelingSummary and Getting Help in JMPExercisesReferences
Part 3 Model Building
Chapter 4 Multiple Linear Regression
In the NewsRepresentative Business ProblemsPreview of End ResultLooking Inside the Black Box: How the Algorithm WorksExample 1: Housing PricesApplying the Business Analytics ProcessSummaryExample 2: Bank RevenuesApplying the Business Analytics ProcessSummaryExercisesReferences

Chapter 5 Logistic Regression
In the NewsRepresentative Business ProblemsPreview of the End ResultLooking Inside the Black Box: How the Algorithm WorksExample 1: Lost Sales OpportunitiesApplying the Business Analytics ProcessExample 2: Titanic PassengersApplying the Business Analytics ProcessSummaryKey Take-Aways and Additional ConsiderationsExercisesReferences
Chapter 6 Decision Trees
In the NewsRepresentative Business ProblemsPreview of the End ResultLooking Inside the Black Box: How the Algorithm WorksClassification Tree for StatusStatistical Details Behind Classification TreesOther General Modeling ConsiderationsExploratory Modeling versus Predictive ModelingModel Cross-ValidationDealing with Missing ValuesDecision Tree Modeling with Ordinal PredictorsExample 1: Credit Card MarketingThe StudyApplying the Business Analytics ProcessCase SummaryExample 2: Printing Press YieldThe StudyApplying the Business Analytics ProcessCase SummarySummaryExercisesReferences
Chapter 7 Neural Networks
In the NewsRepresentative Business ProblemsMeasuring SuccessPreview of the End ResultLooking Inside the Black Box: How the Algorithm WorksNeural Networks with Categorical ResponsesExample 1: ChurnApplying the Business Analytics ProcessModelingThe Neural Model and ResultsCase SummaryExample 2: Credit RiskApplying the Business Analytics ProcessCase SummarySummary and Key Take-AwaysExercisesReferences
Part 4 Model Selection and Advanced Methods
Chapter 8 Using Cross-Validation
OverviewWhy Cross-Validation?Partitioning Data for Cross-ValidationUsing a Random Validation PortionSpecifying the Validation Roles for Each RowK-fold Cross-ValidationUsing Cross-Validation for Model Fitting in JMP ProExampleCreating Training, Validation, and Test SubsetsExamining the Validation SubsetsUsing Cross-Validation to Build a Linear Regression ModelChoosing the Regression Model Terms with Stepwise RegressionMaking PredictionsUsing Cross-Validation to Build a Decision Tree ModelFitting a Neural Network Model Using Cross-ValidationModel ComparisonKey Take-AwaysExercisesReferences
Chapter 9 Advanced Methods
OverviewConcepts in Advanced ModelingBaggingBoostingRegularizationAdvanced Partition MethodsBootstrap ForestBoosted TreeBoosted Neural Network ModelsGeneralized Regression ModelsMaximum Likelihood RegressionRidge RegressionLasso RegressionElastic NetKey Take-AwaysExercisesReferences
Chapter 10 Capstone and New Case Studies
IntroductionCase Study 1: Cell ClassificationStage 1: Define the ProblemStage 2: Prepare for ModelingStage 3: ModelingCase Study 2: Blue Book for Bulldozers (Kaggle Contest)Getting to Know the DataData PreparationModelingModel ComparisonNext StepsCase Study 3: Default Credit Card, Presenting Results to ManagementDeveloping a Management ReportCase Study 4: Carvana (Kaggle Contest)ExercisesReferences
Appendix
Index

Content preview from Building Better Models with JMP Pro

8Using 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

Overview

We first introduced model cross-validation in Chapter 6. In this chapter, we dig more deeply into the concept ...

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