Bontempi Gianluca. Statistical foundations of machine learning

2013.The procedure for finding useful patterns in data is known by different names in different communities but more and more, it is grouped under the label of machine learning. This handbook aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data. This manuscript aims to find a good balance between theory and practice by situating most of the theoretical notions in a real context with the help of practical examples and real datasets. All the examples are implemented in the statistical programming language R.Foundations of probability
Classical parametric estimation
Nonparametric estimation and testing
Statistical supervised learning
The machine learning procedure
Linear approaches
Nonlinear approaches
Model averaging approaches
Feature selection
ConclusionsAppendix