Applied Statistical Learning

Matthias Schonlau is a Professor in the Department of Statistics and Actuarial Science at the University of Waterloo, Canada. Prior to his academic career, he spent 14 years at the RAND Corporation, USA, the Max Planck Institute for Human Development in Berlin, Germany, the German Institute for Economic Analysis (DIW), the National Institute of Statistical Sciences, USA, and AT&T Labs Research, USA. He won the Humboldt Prize and was elected Fellow of the American Statistical Association. He has published more than 80 peer-reviewed articles and is also the lead author of the book Conducting Research Surveys via E-Mail and the Web (RAND Corporation).

• Preface.- 1 Prologue.- 2 Statistical Learning: Concepts.- 3 Statistical Learning: Practical Aspects.- 4 Logistic Regression.- 5 Lasso and Friends.- 6 Working with Text Data.- 7 Nearest Neighbors.- 8 The Naive Bayes Classifier.- 9 Trees.- 10 Random Forests.- 11 Boosting.- 12 Support Vector Machines.- 13 Feature Engineering.- 14 Neural Networks.- 15 Stacking.- Index.