Calorie Burn Prediction Analysis Using XGBoost Regressor and Linear Regression Algorithms

Calorie Burn Prediction Analysis Using XGBoost Regressor and Linear Regression Algorithms

Authors

  • Binumon Joseph ktu
  • Sona P Vinoy

Keywords:

Colab, XGBoost Regressor, Linear regression, machine learning, accuracy

Abstract

The overarching idea of this research project
is to make a comparative study of machine learning
algorithms to predict the calories burn during the
workout. In this paper we first build a machine learning
systems that can predict the amount of calories burnt
during exercise. In today’s world many people are
inquisitive about the workout that they do and the
weight loss plan that they take and how much calorie do
they burn once they workout. To solve this problem we
can use ML alggoirthms such as XGBoost regressor and
Linear Regression.

Author Biography

Binumon Joseph, ktu

 

 

Published

2023-02-23

How to Cite

Binumon Joseph, & Sona P Vinoy. (2023). Calorie Burn Prediction Analysis Using XGBoost Regressor and Linear Regression Algorithms. National Conference on Emerging Computer Applications, 4(1), 187–191. Retrieved from https://ajcejournal.in/nceca/article/view/174
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