Predictive Analytics : The Power to Predict who will Click, Buy, Lie, or Die
Contents
Foreword
Preface to the Revised and Updated Edition
Frequently Asked Questions about Predictive Analytics
Who Is this Book for?
Is the Idea of predictive analytics Hard to Understand?
Is this Book a How-To?
Not a How-To? Then Why Should Techies Read it?
What Is the Purpose of this Book?
How Technical Does this Book Get?
Is this a University Textbook?
How Should I Read this Book?
What's New in the ``Revised and Updated´´ Edition of Predictive Analytics?
Where Can I Learn More After this Book, Such as a How-To for Hands-On Practice?
Preface to the Original Edition
Introduction
Prediction in Big Business-The Destiny of Assets
Introducing . . . the Clairvoyant Computer
``Feed Me!´´-Food for Thought for the Machine
I Knew You Were Going to Do That
The Limits and Potential of Prediction
The Field of Dreams
Organizational Learning
The New Super Geek: Data Scientists
The Art of Learning
Chapter 1: Liftoff! Prediction Takes Action
Going Live
A Faulty Oracle Everyone Loves
Predictive Protection
A Silent Revolution Worth a Million
The Perils of Personalization
Deployment's Detours and Delays
In Flight
Elementary, My Dear: The Power of Observation
To Act Is to Decide
A Perilous Launch
Houston, We Have a Problem
The Little Model That Could
Houston, We Have Liftoff
A Passionate Scientist
Launching Prediction into Inner Space
Chapter 2: With Power Comes Responsibility
The Prediction of Target and the Target of Prediction
A Pregnant Pause
My 15 Minutes
Thrust into the Limelight
You Can't Imprison Something That Can Teleport
Law and Order: Policies and Policing of Data
The Battle over Data
Data Mining Does Not Drill Down
HP Learns about Itself
Insight or Intrusion?
Flight Risk: I Quit!
Insights: The Factors behind Quitting
Delivering Dynamite
The Value Gained from Flight Risk
Predicting Crime to Stop It Before It Happens
The Data of Crime and the Crime of Data
Machine Risk without Measure
The Cyclicity of Prejudice
Good Prediction, Bad Prediction
The Source of Power
Chapter 3: The Data Effect
A Cautionary Tale: Orange Lemons
The Source: Otherwise Boring Logs Fuel Prediction
Social Media and Mass Public Mood
Recycling the Data Dump
The Instrumentation of Everything We Do
Batten Down the Hatches: TMI
Who's Your Data?
The Data Effect: It's Predictive
The Building Blocks: Predictors
Far Out, Bizarre, and Surprising Insights
Caveat 1: Correlation Does Not Imply Causation
Caveat 2: Securing Sound Discoveries
What Went Wrong: Accumulating Risk
The Potential and Danger of Automating Science: Vast Search
A Failsafe for Sound Results
A Prevalent Mistake
Putting All the Predictors Together
Chapter 4: The Machine That Learns
Boy Meets Bank
Bank Faces Risk
Prediction Battles Risk
Risky Business
The Learning Machine
Building the Learning Machine
Learning from Bad Experiences
How Machine Learning Works
Decision Trees Grow on You
Computer, Program Thyself
Learn Baby Learn
Bigger Is Better
Overlearning: Assuming Too Much
The Conundrum of Induction
The Art and Science of Machine Learning
Feeling Validated: Test Data
Carving out a Work of Art
Putting Decision Trees to Work for Chase
Money Grows on Trees
The Recession-Why Microscopes Can't Detect Asteroid Collisions
After Math
Chapter 5: The Ensemble Effect
Casual Rocket Scientists
Dark Horses
Mindsourced: Wealth in Diversity
Crowdsourcing Gone Wild
Your Adversary Is Your Amigo
United Nations
Meta-Learning
A Big Fish at the Big Finish
Collective Intelligence
The Wisdom of Crowds . . . of Models
A Bag of Models
Ensemble Models in Action
The Generalization Paradox: More Is Less
The Sky's the Limit
Chapter 6: Watson and the Jeopardy! Challenge
Text Analytics
Our Mother Tongue's Trials and Tribulations
Once You Understand the Question, Answer It
The Ultimate Knowledge Source
Artificial Impossibility
Learning to Answer Questions
Walk Like a Man, Talk Like a Man
Putting on the Pressure
The Answering Machine
Moneyballing Jeopardy!
Amassing Evidence for an Answer
Elementary, My Dear Watson
Mounting Evidence
Weighing Evidence with Ensemble Models
An Ensemble of Ensembles
Machine Learning Achieves the Potential of Natural Language Processing
Confidence without Overconfidence
The Need for Speed
Double Jeopardy!-Would Watson Win?
Jeopardy! Jitters: Deploying a Prototype
For the Win
After Match: Honor, Accolades, and Awe
Iambic IBM AI
Predict the Right Thing
Chapter 7: Persuasion by the Numbers
Churn Baby Churn
Sleeping Dogs
A New Thing to Predict
Eye Can't See It
Perceiving Persuasion
Persuasive Choices
Business Stimulus and Business Response
The Quantum Human
Predicting Influence with Uplift Modeling
Banking on Influence
Predicting the Wrong Thing
Response Uplift Modeling
The Mechanics of Uplift Modeling
How Uplift Modeling Works
The Persuasion Effect
Influence across Industries
Immobilizing Mobile Customers
Afterword
Tomorrow's Just a Day Away
The Future of Prediction
Appendix A: The Five Effects of Prediction
Appendix B: Twenty Applications of Predictive Analytics
Appendix C: Prediction People-Cast of ``Characters´´
Hands-On Guide
Acknowledgments
About the Author
182 Examples of Predictive Analytics
Index
End User License Agreement