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Machine learning for neuroimaging with scikit-learn. Front Neuroinformatics. 2014;8:14. • We accept pre-submission inquiries • Our selector tool helps you to find the most relevant journal • We provide round the clock customer support • Convenient online

by Re Abraham, Fabian Pedregosa, Michael Eickenberg, Andreas Muller, Jean Kossaifi, Re Gramfort, Re Abraham, Fabian Pedregosa, Michael Eickenberg, Andreas Muller, Hal Id Hal, Re Abraham, Fabian Pedregosa, Michael Eickenberg, Andreas Muller, Jean Kossaifi, Alexandre Abraham
"... HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte p ..."
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HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et a ̀ la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Scikit-learn: Machine learning in Python

by Fabian Pedregosa, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Parietal Inria, Olivier Grisel, Peter Prettenhofer, Ron Weiss, Jake Vanderplas, Mikio Braun - Journal of Machine Learning Research
"... ar ..."
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Abstract not found

experiences from the scikit-learn

by Lars Buitinck, Mathieu Blondel, Fabian Pedregosa, Andreas C. Müller, Olivier Grisel, Vlad Niculae, Peter Prettenhofer, Re Gramfort, Jaques Grobler, Robert Layton, Jake V, Arnaud Joly, Brian Holt, Inria Saclay, Ciuvo Gmbh
"... design for machine learning software: ..."
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design for machine learning software:

Eliasmith C. Hyperopt-sklearn: automatic hyperparameter configuration for scikit-learn

by Brent Komer, James Bergstra, Chris Eliasmith - In: Proceedings of SciPy , 2014
"... Abstract—Hyperopt-sklearn is a new software project that provides automatic algorithm configuration of the Scikit-learn machine learning library. Following Auto-Weka, we take the view that the choice of classifier and even the choice of preprocessing module can be taken together to represent a singl ..."
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Abstract—Hyperopt-sklearn is a new software project that provides automatic algorithm configuration of the Scikit-learn machine learning library. Following Auto-Weka, we take the view that the choice of classifier and even the choice of preprocessing module can be taken together to represent a

Independent consultant

by Lars Buitinck, Mathieu Blondel, Fabian Pedregosa, Andreas C. Müller, Olivier Grisel, Vlad Niculae, Peter Prettenhofer, Re Gramfort, Jaques Grobler, Robert Layton, Jake V, Arnaud Joly, Brian Holt, Gaël Varoquaux, Parietal Inria Saclay, Ciuvo Gmbh , 2013
"... API design for machine learning software: experiences from the scikit-learn project ..."
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API design for machine learning software: experiences from the scikit-learn project

unknown title

by Gaël Varoquaux Parietal Inria Saclay
"... The scikit-learn12 project [4] is an increasingly pop-ular machine learning library written in Python. It is designed to be simple and efficient, useful to both experts and non-experts, and reusable in a variety of contexts. The primary aim of the project is to provide a compendium of efficient impl ..."
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The scikit-learn12 project [4] is an increasingly pop-ular machine learning library written in Python. It is designed to be simple and efficient, useful to both experts and non-experts, and reusable in a variety of contexts. The primary aim of the project is to provide a compendium of efficient

Mathieu Blondel

by Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Rokkodai Nada, Peter Prettenhofer, Ron Weiss, Jake Vanderplas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Édouard Duchesnay, Mikio Braun
"... Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of ..."
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Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease

Machine Learning for Neurological Disorders

by Matthew B. Blaschko
"... The last two decades have seen tremendous advances in our understanding of human brain structure and function, particularly at the level of systems neuroscience, where neuroimaging methods have led to better delineation of brain networks and brain modules. Brain understanding is one of the greatest ..."
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of assessing the impact of different therapeutic strategies. These data are by necessity high dimensional and complex, driving the widespread application of machine learning techniques for their analysis. Machine learning in this context works by learning a regressor from the space of brain recordings (e

SOFTWARE ORIGINAL ARTICLE Wyrm: A Brain-Computer Interface Toolbox in Python

by Bastian Venthur, Johannes Höhne ·hendrik Heller, Benjamin Blankertz, Bastian Venthur , 2015
"... Abstract In the last years Python has gained more and more traction in the scientific community. Projects like NumPy, SciPy, and Matplotlib have created a strong foun-dation for scientific computing in Python and machine lear-ning packages like scikit-learn or packages for data analysis like Pandas ..."
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Abstract In the last years Python has gained more and more traction in the scientific community. Projects like NumPy, SciPy, and Matplotlib have created a strong foun-dation for scientific computing in Python and machine lear-ning packages like scikit-learn or packages for data analysis like Pandas

and the Alzheimers Disease Neuroimaging Initiative † Summary

by Chris Hinrichs A, B Vikas Singh B, Moo K. Chung B, Sterling C. Johnson D
"... Structural and functional brain images are playing an important role in helping us understand the changes associated with neurological disorders such as Alzheimer’s disease (AD). Recent efforts have now started investigating their utility for diagnosis purposes. This line of research has shown promi ..."
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promising results where methods from machine learning (such as Support Vector Machines) have been used to identify AD-related patterns from images, for use in diagnosing new individual subjects. In this paper, we propose a new framework for AD classification which makes use of Linear Program (LP) boosting
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