sriharshitha07/personality_prediction

Personality_prediction

Individual variances in thinking, feeling, and acting patterns are referred to as personality. The majority of people in today's society have social media accounts and send hundreds of messages every day. People frequently utilise social media to express themselves on topics such as their lives and the well-being of their families, psychology, financial concerns, interactions with societies and the environment, and politics. In some situations, these terms can be used to describe a person's personality and conduct. We sought to determine a person's personality based on social media information in this study. We're doing this by employing the Myers-Briggs personality type indicator (MBTI) to categorise people's personalities into different groups. The MBTI personality test is one of the most widely used in the world.

Introversion (I) vs. Extroversion (E), Intuition (N) vs. Sensing (S), Thinking (T) vs. Feeling (F), and Judging (J) vs. Perceiving (P) are the 16 personality types represented in the dataset (P). The introverted, intuitive, sensible, and judging personality type is defined as a person who is introverted, perceptive, reasonable, and judgmental. Logistic Regression, Support Vector Machines (SVM), Nave Bayes, and Random Forest are four machine learning models that we developed. Finally, depending on the findings of assessment metrics, we compare and contrast the results acquired from the machine learning models and determine which one is the best (accuracy score, geometric mean score, ROC-AUC score). The final model employs Logistic Regression since it outperformed the other categorization