Personality Prediction Using Machine Learning

Personality Prediction Using Machine Learning

Author Name : Saurabh Bhaiyyasaheb Pawar, Swapnil Vilas Kotapure, Siddhant Sharad Bachhav, Sumit Sunil Jogdand, Dr. Sivaram Ponnusamy

ABTRACT Personality prediction is a crucial aspect of understanding human behavior, decision-making, and social interactions. The OCEAN model, comprising Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism, is a widely accepted framework for personality assessment. The concept of using ocean models to predict personality traits based on machine learning (ML) is an emerging field in the intersection of psychology, computer science, and physics. The Ocean Model theory suggests that personality traits can be viewed as a set of interconnected waves or patterns that ebb and flow over time, much like the oceans tides. We collected a dataset of participants’ responses to a personality questionnaire and applied various machine learning algorithms, including K- Means Clustering, Gaussian Mixture Model to predict their personality scores. Our results show that the proposed approach achieves high accuracy in predicting personality traits, with showing the highest prediction accuracy. The study demonstrates the potential of machine learning in personality prediction and provides insights into the relationships between personality traits and behavioral patterns. The findings have implications for applications in human resources, marketing, and mental health. This abstract presents an overview of the Ocean Model theory, its potential applications in personality assessment, and the challenges and limitations associated with this approach.