Lien ebook : https://link-springer-com.ezproxy.univ-catholille.fr/book/10...

ISBN 13 : 978-0387848570

Sommaire : 1 Introduction

2 Overview of Supervised Learning
3 Linear Methods for Regression
4 Linear Methods for Classification
5 Basis Expansions and Regularization
6 Kernel Smoothing Methods
7 Model Assessment and Selection
8 Model Inference and Averaging
9 Additive Models, Trees, and Related Methods
10 Boosting and Additive Trees
11 Neural Networks
12 Support Vector Machines and Flexible Discriminants
13 Prototype Methods and Nearest-Neighbors
14 Unsupervised Learning
15 Random Forests
16 Ensemble Learning
17 Undirected Graphical Models
18 High-Dimensional Problems

References
Author Index
Index

Nbre volumes : 0

Langue : Anglais

Collection : SERIES IN STATISTICS

Edition : 2ème

Localisation : Bibliothèque Campus de Nice

Support : Numérique

Etat : Présent

Propriétaire : Bibliothèque