Nowadays, the importance of mental health has become an increasinglyrelevant theme. Psychological assessments are part of thedaily life of clinical psychologists in order to identify possible issuesto be explored. Therefore, this work presents a preliminarystudy which aims to evaluate the accuracy of machine learningalgorithms for the detection of the predominant factor of big fivepersonality test. Real answers from a dataset were considered in thecomputational experiments, and two machine learning algorithmswere evaluated: the K-Nearest Neighbors (KNN) and the K-means.Results show that both algorithms could accurately detect the pedominantfactor of the big five test, and KNN obtained better resultsthan the other algorithm.
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