A machine learning model that uses PCA and K-Means to analyze responses of an individual to a standardized personality assessment questionnaire in order to accurately predict their scores for each of the Big Five personality traits in the OCEAN test. The goal of the model would be to predict an individual's personality scores with a high degree of accuracy based on their demographic information and their responses to the questionnaire.
The dataset used consists of 1,015,342 questionnaire answers collected online by Open Psychometrics. Dataset Specific questions are asked for each personality trait, and participants must choose between 1 and 5.
Dataset link: https://www.kaggle.com/datasets/tunguz/big-five-personality-test
The potential applications of this personality prediction model using ML and the Big Five are numerous. For example, in the field of human resources, such a model could be used to improve the accuracy of employee selection and promotion processes by identifying individuals who are likely to perform well in a particular job based on their personality traits. In marketing, personality prediction could be used to develop more personalized advertising campaigns and product recommendations based on an individual's personality profile. In mental health, a personality prediction model could help identify individuals who are at risk for certain psychological disorders, allowing for earlier intervention and treatment.