Training a Machine Learning Model to Recognize Signs of Depression

Many people have not had a professional diagnosis, and could have depression without being aware of it. To attempt to answer this question, I used a person’s daily habits and how they change, and attempt to predict if they will experience a depressive episode in the future.

Depression is a common mental disorder yet can severely damage your everyday habits and health. It is also difficult to diagnose without a professional assessment, so it can be hard to identify whether or not you have it. However, some everyday habits, and changes in those habits, can be indicative of future depressive episodes. Pinpointing those features, I trained a KNN and decision tree based models to predict whether or not someone would have a depressive episode in the future. The best performing model was a KNN model which had an accuracy of 70%, with an F1 score of 69%. These statistics, while not insignificant, still need to be improved on before they can be used as a reliable predictor of depression.