Methodology for Reducing the Number of Psychological Test Questions for Use in a Predictive Machine Learning Model

The article describes an approach to reducing the number of questions in the Keys to Personal Mastery Inventory (KPMI) psychological testing questionnaire with the further addition of missing data and their use in a machine learning model to predict respondent satisfaction with their job. Since the 30s of the 20th century, mathematicians, physicists and engineers have been working on the description of traffic flows. But theoretical models do not work well because a person is driving a car, and a person is unpredictable. In the same situation, it behaves differently. This work aims to reduce driver uncertainty using machine learning methods.