TY  - BOOK
AU  - Hastie, Trevor  
AU  - Tibshirani, Robert 
AU  - Friedman, Jerome 
TI  - The Elements of Statistical Learning: Data Mining, Inference, and Prediction
SN  - 9780387848570
U1  - 006.3122 2nd ed.
PY  - 2017///
CY  - New YORK
PB  - Springer
KW  - Artificial intelligence Bioinformatics Data mining
KW  - Electronic data processing
N1  - Contenido: Overview of supervised learning. 
Linear methods for regression. 
Linear methods for classification. 
Basis expansions and regularization. 
Kernel smoothing methods. 
Model assessment and selection. 
Model inference and averaging. 
Additive models, trees, and related methods. 
Boosting and additive trees. 
Neural networks. 
Support vector machines and flexible discriminants. 
Prototype methods and nearest-neighbors. 
Unsupervised learning. 
Random forests. 
Ensemble learning. 
Undirected graphical models. 
High-dimensional problems
ER  -