Comparison Of Various Machine Learning Techniques Used To Classify Obesity
Abstract
Estimating obesity rates is a crucial issue in the medical sector since it may help those who want to slim down or maintain their fitness by offering helpful advice. The essay looks for a model that can forecast obesity and gives readers advice on how to stay underweight. To be more precise, dimension reduction was used in this research to streamline the data set and Principal Component Analysis (PCA) was used to try to identify the most important aspect of obesity based on the data set. Additionally, the article utilised machine learning techniques like Support Vector Machine (SVM).
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