Machine Learning for Email

Preface;
Machine Learning for Hackers: Email;
How This Book is Organized;
Conventions Used in This Book;
Using Code Examples;
Safari® Books Online;
How to Contact Us;
Chapter 1: Using R;
1.1 R for Machine Learning;
1.2 Further Reading on R;
Chapter 2: Data Exploration;
2.1 Exploration vs. Confirmation;
2.2 What is Data?;
2.3 Inferring the Types of Columns in Your Data;
2.4 Inferring Meaning;
2.5 Numeric Summaries;
2.6 Means, Medians, and Modes;
2.7 Quantiles;
2.8 Standard Deviations and Variances;
2.9 Exploratory Data Visualization;
2.10 Visualizing the Relationships between Columns;
Chapter 3: Classification: Spam Filtering;
3.1 This or That: Binary Classification;
3.2 Moving Gently into Conditional Probability;
3.3 Writing Our First Bayesian Spam Classifier;
Chapter 4: Ranking: Priority Inbox;
4.1 How Do You Sort Something When You Don’t Know the Order?;
4.2 Ordering Email Messages by Priority;
4.3 Writing a Priority Inbox;
Works Cited;