CALORIE BURN PREDICTION
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Date
2023-06-10
Journal Title
Journal ISSN
Volume Title
Publisher
University of M'sila
Abstract
Life is all about finding balance. and that's most important when it comes to our body. However,
staying fit and healthy necessitates frequent physical activity. The variety of burned energy in daily
life is directly related to weight maintenance, weight gain, or weight loss. people need to know how
many
calories they burned each day. Our project is predicting the calorie burned during the workout with
the use of machine learning algorithm XGBoost regressor model approach to produce accurate
results. the model is fed with more than 15000 data and its mean absolute error is 1.48. Therefore, we
built a mobile application that help the users easily by put their values obtain results of burned calorie.
Description
Keywords
XGBoost regressor, machine learning, accurate.