By browsing this website, you acknowledge the use of a simple identification cookie. It is not used for anything other than keeping track of your session from page to page. OK


Search

1

The elements of statistical learning: data mining, inference, and prediction.

HASTIE Trevor ; TIBSHIRANI Robert ; FRIEDMAN Jerome

SPRINGER

2009

745

212.65-HASTI

MATHEMATICAL STATISTICS ; PROBABILITIES


Number of copies : 1
No. Call n° Bar code Commentary
1 [available]

Comment :

ISBN 13 : 978-0387848570

Contents :
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

Language : English

Series : SERIES IN STATISTICS

Print : 2ème

Location : Nice Library

Material : Paper

Statement : Présent

Owner : Bibliothèque