Alcohol Consumption Rate Prediction using Machine Learning Algorithms

Consumption of alcohol among students, mainly college or university students, has risen immensely over the past couple of years. It has been determined that students experiment with alcohol during their college years and around 80% of students consume alcohol in some manner or degree and 50% are involved in binge drinking. This is mainly due to students wanting to explore their newfound independence and freedom which they didn't have during their school years. In this paper, we have analyzed students belonging to two courses of a Secondary School-Maths and Portuguese Language Course. We have applied Feature Scaling along with various machine learning classification models to determine higher alcohol consumption where the Random Forest Model outperformed all other models that have been applied such as Linear, Ridge, and Lasso Regression, Decision Tree, k-NN, XG Boost, Support Vector Machine, ADA Boosting Regressor and Gradient Boosting Regressor for analysis of alcohol consumption among secondary school students.