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Data Study Group Final Report: Codecheck

Data Study Group team

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  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.1415344", 
  "language": "eng", 
  "title": "Data Study Group Final Report: Codecheck", 
  "issued": {
    "date-parts": [
  "abstract": "<p>Data Study Groups are week-long events at The Alan Turing Institute&nbsp;bringing together some of the country&rsquo;s top talent from data science, artificial intelligence, and wider fields, to analyse real-world data science challenges.</p>\n\n<p><strong>CodeCheck: How do our food choices affect climate change?</strong></p>\n\n<p>Different approaches were proposed to predict the carbon footprint of products from the different datasets provided by CodeCheck.</p>\n\n<p>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.</p>\n\n<p>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.</p>", 
  "author": [
      "family": "Data Study Group team"
  "type": "article", 
  "id": "1415344"
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