ScienceOpen:
research and publishing network
For Publishers
Discovery
Metadata
Peer review
Hosting
Publishing
For Researchers
Join
Publish
Review
Collect
My ScienceOpen
Sign in
Register
Dashboard
Blog
About
Search
Advanced search
My ScienceOpen
Sign in
Register
Dashboard
Search
Search
Advanced search
For Publishers
Discovery
Metadata
Peer review
Hosting
Publishing
For Researchers
Join
Publish
Review
Collect
Blog
About
9
views
0
references
Top references
cited by
87
0 reviews
Review
0
comments
Comment
0
recommends
+1
Recommend
0
collections
Add to
0
shares
Share
Twitter
Sina Weibo
Facebook
Email
2,962
similar
All similar
Record
: found
Abstract
: not found
Article
: not found
Scikit-learn: Machine learning in Python
Author(s):
F Pedregosa
,
G Varoquaux
,
A Gramfort
,
V MICHEL
,
B Thirion
,
O Grisel
,
M. BLONDEL
,
P. Prettenhofer
,
R Weiss
,
V. Dubourg
,
F. PEDREGOSA
,
V Michel
,
M. Blondel
,
À Pedregosa
,
R. WEISS
,
V Mueller
,
G. Varoquax
,
RA Weiss
Publication date:
2011
Journal:
The J Machine Learn Res
Read this article at
ScienceOpen
Bookmark
There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.
Related collections
Annual Reviews AI, Machine Learning, and Society
Data availability:
ScienceOpen disciplines:
Computational chemistry & Modeling
Comments
Comment on this article
Sign in to comment
Similar content
2,962
Scikit-ribo Enables Accurate Estimation and Robust Modeling of Translation Dynamics at Codon Resolution
Authors:
Han Fang
,
Aditya Radhakrishnan
,
Adam Siepel
…
Hands-On Machine Learning With Scikit-Learn, Keras, and TensorFlow
Authors:
A. Gerón
Hands-on Machine Learning with Scikit-Learn, Keras and Tensor Flow
Authors:
A. Gerón
,
A. Géron
,
Géron A
See all similar
Cited by
87
Meta-analysis of gut microbiome studies identifies disease-specific and shared responses
Authors:
Claire Duvallet
,
Sean M. Gibbons
,
Thomas Gurry
…
Big-Data Science in Porous Materials: Materials Genomics and Machine Learning
Authors:
Kevin Jablonka
,
Daniele Ongari
,
Seyed Moosavi
…
BioSeq-Analysis2.0: an updated platform for analyzing DNA, RNA and protein sequences at sequence level and residue level based on machine learning approaches
Authors:
Bin Liu
,
Xin Gao
,
Hanyu Zhang
See all cited by