The Predictive Five: Supervised learning approach to personality psychology
Current research in psychology has suggested that people’s personalities can be effectively captured using five broad dimensions (the Big Five Model).However, the Big Five model has been criticized for its relatively limited ability to predict meaningful outcomes in human life. We propose a novel approach towards modeling human personality that is based on the maximization of the model’s predictive accuracy. We used supervised machine learning methods and psychological big data to develop an alternative to the Big Five which we call the Predictive Five. Our results suggest that this model outperforms the Big Five in terms of its ability to predict people’s thoughts, feelings, and behaviors. The approach described herein could revolutionize the field of personality research, and improve psychological scientists’ ability to predict future outcomes, and thereby help people steer their lives towards desired paths.
The attachments are part of the work described above. There are 9 data preparation files, one for each variable, with the file named svq for two Schwartz metric variables.
In the joining file you can find the application of the RRR algorithm. In the CV files you can find the application for the linear regression models.
Here for any questions,