Machine Learning Approach to Predict Influence of Smoking on Student Life

Smoking is one of the measure factors to distract student life, also a leading factor for many diseases in the recent era, where many university students take this habit as a fashion. In Bangladesh, 35% of grown-ups are now consuming tobacco either smoked and/or in smokeless form according to a World Health Organization report. This is because our study to find out the reason behind it and the consequence of smoking on graduate student's life. This study focused on different attributes of student life to find out the impacts of smoking in their academic life. We got most of the students who used to do smoke did not get better results in their academic life. As a result, they cannot be able to build their desire future. However, we tested many algorithms, wefound the same accuracy of two algorithms those are KNN and random forest. We got 87.93% of accuracy from applying those two algorithms from our collected dataset.