Calories Burnt Prediction using Machine Learning

Abstract: Using machine learning (ML) techniques, this study examines the prediction of calories burnt based on various physiological and activity-related parameters. The study employs classification and regression algorithms to forecast calorie expenditure by analysing datasets containing attributes such as age, weight, heart rate, and exercise duration. The results highlight key influencing factors and contribute to a deeper understanding of how machine learning can enhance predictive modelling in health and fitness research.

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Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-04-29
DOI
https://doi.org/10.22214/ijraset.2025.69728
Citations
5
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
1.01
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article

Calories Burnt Prediction using Machine Learning

Abu Rayyan
5 citations
International Journal for Research in Applied Science and Engineering Technology
Traffic Prediction and Management Techniques
1.01
article

Calories Burnt Prediction using Machine Learning

Abu Rayyan
article en
5 citations

Abstract

Abstract: Using machine learning (ML) techniques, this study examines the prediction of calories burnt based on various physiological and activity-related parameters. The study employs classification and regression algorithms to forecast calorie expenditure by analysing datasets containing attributes such as age, weight, heart rate, and exercise duration. The results highlight key influencing factors and contribute to a deeper understanding of how machine learning can enhance predictive modelling in health and fitness research.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(4)
Noida International University (IN)
Openalex Percentile: Top 26%
Traffic Prediction and Management Techniques
1.01
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