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Insights From Machine-Learned Diet Success Prediction, Ingmar Weber, Palakorn Achananuparp
Insights From Machine-Learned Diet Success Prediction, Ingmar Weber, Palakorn Achananuparp
Research Collection School Of Computing and Information Systems
To support people trying to lose weight and stay healthy, more and more fitness apps have sprung up including the ability to track both calories intake and expenditure. Users of such apps are part of a wider “quantified self“ movement and many opt-in to publicly share their logged data. In this paper, we use public food diaries of more than 4,000 long-term active MyFitnessPal users to study the characteristics of a (un-)successful diet. Concretely, we train a machine learning model to predict repeatedly being over or under self-set daily calories goals and then look at which features contribute to the …