Comparison of Various ML Algorithms for Predicting Personality Using Balanced Bagging Classifier

Understanding people's personalities makes it easier to understand their ideas, beliefs, emotions, and reactions to particular circumstances. Regardless of the kind of relationship (friends, employer and employee, seller and buyer, etc.), it would benefit all parties and possibly result in improved relationships. The popularity of community media as a means of assertiveness and awareness has raised curiosity around the Myers-Briggs type Indicator (MBTI), a tool for analysing personality traits. In research, we have implemented three machine learning algorithms logistic regression, linear support vector classification and random forest. We also practised balanced bagging classifier to cope with the imbalanced data. The investigation found that machine learning algorithm understand and classify the personality well with balanced bagging classifier. In all the three algorithm logistic regression generates good F1 score with balanced bagging algorithm.