Orgnization of this book

Basis

Chapter 02

Basic Conceptions

K-nearest neighbor classifier

Linear Methods

Classical methods

Chapter 03

linear regression

Chapter 04

Logistic Regression

Linear discriminant analysis

Some Improvements

Chapter 06

Stepwise selection

ridge regression

principal components regression

partial least squares

lasso

Validation

Chapter 05

Used to estimate the accuracy (Validity) of a number of different methods

Cross-validation

Bootstrap

Non-linear Methods

Chapter 07

non-linear methods for a single input variable

Chapter 08

tree-based methods

bagging

boosting

random forests

Support vector machines

Chapter 09

Methods for linear and non-linear Classification

Chapter 10

no output variable

principal components analysis

K-means clustering

hierarchical clustering