Reza Drikvandi
CodeCheck: How do our food choices affect climate change?
Drikvandi, Reza; Williams, Angus; Boustati, Ayman; Ezer, Daphne; Arenas, Diego; de Wiljes, Jan-Hendrik; Chang, Marina; Varga, Marton; Groves, Matthew; Ceritli, Taha
Authors
Angus Williams
Ayman Boustati
Daphne Ezer
Diego Arenas
Jan-Hendrik de Wiljes
Marina Chang
Marton Varga
Matthew Groves
Taha Ceritli
Abstract
Different approaches were proposed to predict the carbon footprint of products from the different datasets provided by CodeCheck. Multivariate linear regression and random forest regression models perform well in predicting carbon footprint, especially when - in addition to the nutrition information - the product categories, learned through Latent Dirichlet Allocation (LDA), were used as extra features in the models. The prediction accuracy of the models that were considered varied across datasets. A potential way to display the footprint estimates in the app was proposed.
Citation
Drikvandi, R., Williams, A., Boustati, A., Ezer, D., Arenas, D., de Wiljes, J., …Ceritli, T. (2018). CodeCheck: How do our food choices affect climate change?
Report Type | Project Report |
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Online Publication Date | Sep 13, 2018 |
Publication Date | 2018-09 |
Deposit Date | Oct 6, 2020 |
Publicly Available Date | Nov 2, 2020 |
DOI | https://doi.org/10.5281/zenodo.1415344 |
Additional Information | Journal Name: The Alan Turing Institute Publisher: The Alan Turing Institute Type: monograph Subtype: project_report |
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