Reducing affliction using paternity bearing and addiction of digital gadgets by classification algorithm

Nowadays, stress is a major issue for juvenile. Stress means, the changes in human behavior or physical behavior. For juvenile stress can turns on biological, chemical and hormonal changes. In this paper, the stress of juvenile can be predicted according to the paternity behavior. Due to digitalized world everybody is in need of digital gadgets like Play station, Tablet, Smart Phones and many gaming devices. The stress of teens is measured due to more usage of Digital gadgets. Bayesian classification is a effective method for prediction, it gives more efficiency than other algorithms in computing. The model is developed by supervised learning methodology. The possibility of stress is more for a juvenile, it leads to severe depression, addiction to drugs or committing suicides, effecting physical health, effecting academic output etc. This research paper will target to avoid such complication of teenagers stress. Using the model, stress of each teenager will be predicted and further reference will be provided for counseling or treatment and also increasing parental care to juvenile. Supervised learning methodology is applied for the efficiency of Stress predictor. This research papers is a new methodology to predict stress exclusively for teen agers.