Machine Learning Classifies the Smoking and Drinking Impact

Abstract

This research main objective of this paper is to show the impact of the smoking and drinking habits on our body and making comparative analysis between algorithms to find out which algorithm provides better accuracy. With the help of techniques such as EDA we find out the relationship between the smoking and drinking habits and how interrelated one habit is to another and with the help of Data Visualization techniques we’ll be using such as graphs and other methods to show data visually for better understanding. Algorithms like Logistic Regression, Random Forest, XGBoost, LGBM classifier are used for comparative analysis and the main intention of the paper is to raise awareness in the society that how dangerous these habits are, showing them the impact of these habits having on our body