An analysis on the effects of parenting style on offspring’s behavior using machine learning

Abstract

Parents are usually the most important person for a human being as they encourage and support an offspring’s physical, emotional, social, and intellectual development from infancy to maturity. An individual faces various challenges as they grow up. Proper parenting plays a prominent role in handling and abating those challenges. This paper aims to show various consequences on the attachment style and handling of depression, anxiety, stress, anger due to different types of parenting style. These consequences of parenting styles are to be figured out in an automated way so that one can acknowledge these factors on their own and bring various positive changes to their parenting. The term ”parenting style” refers to a collection of tactics that have various effects on children. These methods can have an impact on children’ minds that lasts long into adulthood, both positively and negatively. This research makes use of machine learning algorithms in order to differentiate between various parenting styles through various aspects of their life such as stress, anxiety, depression, attachment style, anger management etc. The lack of publicly accessible data prompted us to compile my own data set, which consisted of 2206 survey responses from students(school, college, university). Afterward, the survey data was stored and pre-processed. Then, machine learning algorithms such as Decision Tree, XG-BOOST, KNN, Support Vector Machine and Random Forest are utilized to detect parenting style by analyzing the effects of parenting on their offspring and the accuracy of these models are 84.70%, 76.71%, 87.30%, 87.30% and 85.185% sequentially.