Prediction of Mental Disorder Issues In Player unknown’s Battlegrounds (PUBG) using Ridge Regression (RR) and Multi Layer Perception (MLP) Model

Abstract

In the last several decapods, there have been more cases than usual of identifying mental disease and depression. On Twitter, Facebook, and online forums, you can find signs of mental illness, and automatic systems are getting better and better at finding inactivity and other mental diseases. This study surveys recent research that sought to use social media to identify depression and other mental illnesses. The use of screening surveys, their community distribution of analyses on Twitter, or through their participation in online forums have already been used to draw attention to mentally ill individuals. They have also been shown to be easily identifiable by patterns in their language and online behaviour. Many automated detection techniques can be used to identify depressed users on social media. . In addition a number of authors experience that various Social Networking Sites activities may be linked to low self-confidence, particularly in young people and adolescents. In our project the mental disorder is predicted by algorithms namely Ridge Regression (RR) and Multi Layer Perceptron (MLP). We can prove that MLP works better than RR algorithm in terms of accuracy.