ABSTRACT
Nowadays, the importance of mental health has become an increasingly
relevant theme. Psychological assessments are part of the
daily life of clinical psychologists in order to identify possible issues
to be explored. Therefore, this work presents a preliminary
study which aims to evaluate the accuracy of machine learning
algorithms for the detection of the predominant factor of big five
personality test. Real answers from a dataset were considered in the
computational experiments, and two machine learning algorithms
were evaluated: the K-Nearest Neighbors (KNN) and the K-means.
Results show that both algorithms could accurately detect the pedominant
factor of the big five test, and KNN obtained better results
than the other algorithm.