Bandicoot: A python toolbox for mobile phone metadata
Name
15-593.pdf
Size
900.99 KB
Format
Adobe PDF
Checksum (MD5)
82090dba4824b8a1f9fdaec3284a27c2
Author(s)
Rocher, Luc
de Montjoye, Yves-Alexandre
Pentland, Alex Paul
Date Issued
October 2016
Journal
Journal of Machine Learning Research
Publisher
JMLR, Inc.
Citation
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
Version
Final published version
Abstract
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
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
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.
Persistent DSpace Link
DOI of Published Version
http://www.jmlr.org/papers/v17/15-593.html
