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Scikit-learn: Machine Learning in Python
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instance of
scholarly article
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title
Scikit-learn: Machine Learning in Python
(English)
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main subject
scikit-learn
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machine learning
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based on heuristic
inferred from title
Python
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author
Gaël Varoquaux
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2
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David Cournapeau
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13
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Alexandre Gramfort
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3
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Bertrand Thirion
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5
object named as
Bertrand Thirion
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Mathieu Blondel
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7
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Fabian Pedregosa
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1
object named as
Fabian Pedregosa
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Vincent Michel
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4
object named as
Vincent Michel
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Olivier Grisel
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6
object named as
Olivier Grisel
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Peter Prettenhofer
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8
object named as
Peter Prettenhofer
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author name string
Ron Weiss
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9
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Vincent Dubourg
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10
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Jake Vanderplas
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11
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Alexandre Passos
series ordinal
12
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Matthieu Brucher
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14
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Matthieu Perrot
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15
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Édouard Duchesnay
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16
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language of work or name
English
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publication date
October 2011
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number of pages
6
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official website
https://www.jmlr.org/papers/v12/pedregosa11a.html
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full work available at URL
http://www.jmlr.org/papers/volume12/pedregosa11a/pedregosa11a.pdf
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http://jmlr.csail.mit.edu/papers/v12/pedregosa11a.html
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published in
Journal of Machine Learning Research
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volume
12
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page(s)
2825-2830
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describes a project that uses
scikit-learn
1 reference
based on heuristic
inferred from title
Python
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based on heuristic
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maintained by WikiProject
WikiProject Software
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cites work
LIBLINEAR: A Library for Large Linear Classification
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Regularization Paths for Generalized Linear Models via Coordinate Descent
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Result Analysis of the NIPS 2003 Feature Selection Challenge
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PyMVPA: A python toolbox for multivariate pattern analysis of fMRI data
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A supervised clustering approach for fMRI-based inference of brain states
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The NumPy Array: A Structure for Efficient Numerical Computation
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Modular Toolkit for Data Processing (MDP): A Python Data Processing Framework
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