Browse
Publications
Preprints
About
About UCL Open: Env.
Aims and Scope
Editorial Board
Indexing
APCs
How to cite
Publishing policies
Editorial policy
Peer review policy
Equality, Diversity & Inclusion
About UCL Press
Contact us
For authors
Information for authors
How it works
Benefits of publishing with us
Submit
How to submit
Preparing your manuscript
Article types
Open Data
ORCID
APCs
Contributor agreement
For reviewers
Information for reviewers
Review process
How to peer review
Peer review policy
My ScienceOpen
Sign in
Register
Dashboard
Search
Browse
Publications
Preprints
About
About UCL Open: Env.
Aims and Scope
Editorial Board
Indexing
APCs
How to cite
Publishing policies
Editorial policy
Peer review policy
Equality, Diversity & Inclusion
About UCL Press
Contact us
For authors
Information for authors
How it works
Benefits of publishing with us
Submit
How to submit
Preparing your manuscript
Article types
Open Data
ORCID
APCs
Contributor agreement
For reviewers
Information for reviewers
Review process
How to peer review
Peer review policy
My ScienceOpen
Sign in
Register
Dashboard
Search
51
views
0
references
Top references
cited by
328
Cite as...
0 reviews
Review
0
comments
Comment
0
recommends
+1
Recommend
0
collections
Add to
0
shares
Share
Twitter
Sina Weibo
Facebook
Email
2,538
similar
All similar
Record
: found
Abstract
: not found
Book
: not found
The Elements of Statistical Learning
other
Author(s):
Trevor Hastie
,
Jerome Friedman
,
Robert Tibshirani
Publication date
(Print):
2001
Publisher:
Springer New York
Read this book at
Publisher
Buy book
Review
Review book
Invite someone to review
Bookmark
Cite as...
There is no author summary for this book yet. Authors can add summaries to their books on ScienceOpen to make them more accessible to a non-specialist audience.
Related collections
Trace Elements and Electrolytes
Author and book information
Book
ISBN (Print):
978-1-4899-0519-2
ISBN (Electronic):
978-0-387-21606-5
Publication date (Print):
2001
DOI:
10.1007/978-0-387-21606-5
SO-VID:
6b2204bc-1f48-44b5-b203-8fe5b31284fa
History
Data availability:
Comments
Comment on this book
Sign in to comment
Book chapters
pp. 1
Introduction
pp. 9
Overview of Supervised Learning
pp. 41
Linear Methods for Regression
pp. 79
Linear Methods for Classification
pp. 115
Basis Expansions and Regularization
pp. 165
Kernel Methods
pp. 193
Model Assessment and Selection
pp. 225
Model Inference and Averaging
pp. 257
Additive Models, Trees, and Related Methods
pp. 299
Boosting and Additive Trees
pp. 347
Neural Networks
pp. 371
Support Vector Machines and Flexible Discriminants
pp. 411
Prototype Methods and Nearest-Neighbors
pp. 437
Unsupervised Learning
Similar content
2,538
Effects of temperature and ionic strength on the stabilities of the first and second fluoride complexes of yttrium and the rare earth elements
Authors:
Yanxin Luo
,
F.J. Millero
,
Y. LUO
Meiotic sister chromatid cohesion in holocentric sex chromosomes of three heteropteran species is maintained in absence of axial elements.
Authors:
J Suja
,
Eduardo J A M Santos
,
L Cerro
…
An air quality evaluation model for the industrial park based on the fuzzy matter-element analysis
Authors:
See all similar
Cited by
875
Permutation importance: a corrected feature importance measure.
Authors:
André Altmann
,
Laura Toloşi
,
Oliver Sander
…
Hyperspectral Remote Sensing Data Analysis and Future Challenges
Authors:
Gustavo Camps-Valls
,
José Bioucas-Dias
,
Antonio Plaza
…
A primer on deep learning in genomics
Authors:
James Zou
,
Mikael Huss
,
Abubakar Abid
…
See all cited by