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2016 JMLR JMLR 2016

bandicoot: a Python Toolbox for Mobile Phone Metadata

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 classification and clustering tasks. Emphasis is put on ease of use, consistency, and documentation. bandicoot has no dependencies and is distributed under MIT license. [abs] [ pdf ][ bib ] © JMLR 2016. (edit, beta)

🧭 Keyword Pioneer — mobile phone metadatum
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio
🌉 Interdisciplinary Bridge — Data Science & Analytics and Machine Learning
🐣 Hot Topic Early Bird — time series analysis

Authors

Yves-Alexandre De Montjoye , Luc Rocher , Alex Sandy Pentland

Topics

Machine Learning > Core Methods > Classification Machine Learning > Core Methods > Clustering Machine Learning > Core Methods > Representation Learning Data Science & Analytics > Applications > Clustering Machine Learning > Core Methods > Feature Learning

Keywords

time series analysis feature extraction mobile phone metadatum classification clustering python toolbox
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