PERSONALITY PREDICTION USING ML

Computer Engineering

Personality prediction plays a vital role in understanding human behavior, decision-making, and social dynamics. The OCEAN model comprising Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism is a widely recognized framework for assessing personality traits. Integrating this model with machine learning (ML) represents a promising interdisciplinary approach, blending psychology, computer science, and data analysis. The Ocean Model theory conceptualizes personality traits as dynamic, wave-like patterns that shift over time, similar to ocean tides. By analyzing these behavioral fluctuations through ML algorithms, it becomes possible to predict individual personality traits with high precision. This study introduces a machine learning-based method to predict personality using participant responses from a personality questionnaire. Algorithms such as K-Means Clustering and Gaussian Mixture Model (GMM) were employed to classify and forecast personality scores.The results demonstrate strong predictive accuracy, with one model outperforming the rest. The study highlights the effectiveness of ML in personality assessment and its potential applications in domains like human resources, marketing, and mental health. It also outlines key challenges and future directions for refining this innovative approach.

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