Bandicoot: A python toolbox for mobile phone metadata

bandicoot is an open-source Python toolbox to extract more than 1442 features from standard mobile phone metadata. bandicoot makes it easy for machine learning researchers and practitioners to load mobile phone data, to analyze and visualize them, and to extract robust features which can be used for...

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Main Authors: Rocher, Luc, de Montjoye, Yves-Alexandre, Pentland, Alex Paul
Other Authors: Massachusetts Institute of Technology. Media Laboratory
Format: Article
Published: JMLR, Inc. 2018
Online Access:http://hdl.handle.net/1721.1/115988
https://orcid.org/0000-0001-9086-589X
https://orcid.org/0000-0002-8053-9983
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author Rocher, Luc
de Montjoye, Yves-Alexandre
Pentland, Alex Paul
author2 Massachusetts Institute of Technology. Media Laboratory
author_facet Massachusetts Institute of Technology. Media Laboratory
Rocher, Luc
de Montjoye, Yves-Alexandre
Pentland, Alex Paul
author_sort Rocher, Luc
collection MIT
description bandicoot is an open-source Python toolbox to extract more than 1442 features from standard mobile phone metadata. bandicoot makes it easy for machine learning researchers and practitioners to load mobile phone data, to analyze and visualize them, and to extract robust features which can be used for various classiffication and clustering tasks. Emphasis is put on ease of use, consistency, and documentation. bandicoot has no dependencies and is distributed under MIT license. 2016 Yves-Alexandre de Montjoye, Luc Rocher, and Alex 'Sandy' Pentland. Keywords: Python, feature engineering, mobile phone metadata, CDR, visualization
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spelling mit-1721.1/1159882022-09-29T15:50:40Z Bandicoot: A python toolbox for mobile phone metadata Rocher, Luc de Montjoye, Yves-Alexandre Pentland, Alex Paul Massachusetts Institute of Technology. Media Laboratory Program in Media Arts and Sciences (Massachusetts Institute of Technology) de Montjoye, Yves-Alexandre Pentland, Alex Paul bandicoot is an open-source Python toolbox to extract more than 1442 features from standard mobile phone metadata. bandicoot makes it easy for machine learning researchers and practitioners to load mobile phone data, to analyze and visualize them, and to extract robust features which can be used for various classiffication and clustering tasks. Emphasis is put on ease of use, consistency, and documentation. bandicoot has no dependencies and is distributed under MIT license. 2016 Yves-Alexandre de Montjoye, Luc Rocher, and Alex 'Sandy' Pentland. Keywords: Python, feature engineering, mobile phone metadata, CDR, visualization 2018-05-30T18:25:11Z 2018-05-30T18:25:11Z 2016-10 2016-08 2018-02-23T15:41:49Z Article http://purl.org/eprint/type/JournalArticle 1532-4435 1533-7928 http://hdl.handle.net/1721.1/115988 de Montjoye, Yves-Alexandre, Luc Rocher, and Alex Sandy Pentland. "Bandicoot: a Python Toolbox for Mobile Phone Metadata." Journal of Machine Learning Research, 17, 2016, pp. 1-5. © 2016 Yves-Alexandre de Montjoye, Luc Rocher, and Alex ‘Sandy’ Pentland https://orcid.org/0000-0001-9086-589X https://orcid.org/0000-0002-8053-9983 http://www.jmlr.org/papers/v17/15-593.html Journal of Machine Learning Research Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf JMLR, Inc. Journal of Machine Learning Research
spellingShingle Rocher, Luc
de Montjoye, Yves-Alexandre
Pentland, Alex Paul
Bandicoot: A python toolbox for mobile phone metadata
title Bandicoot: A python toolbox for mobile phone metadata
title_full Bandicoot: A python toolbox for mobile phone metadata
title_fullStr Bandicoot: A python toolbox for mobile phone metadata
title_full_unstemmed Bandicoot: A python toolbox for mobile phone metadata
title_short Bandicoot: A python toolbox for mobile phone metadata
title_sort bandicoot a python toolbox for mobile phone metadata
url http://hdl.handle.net/1721.1/115988
https://orcid.org/0000-0001-9086-589X
https://orcid.org/0000-0002-8053-9983
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