5:20 PM - 5:40 PM
[2P5-J-2-01] Prediction of depressive tendencies from health data considered unassociated with depressive states
Keywords:Machine Learning, Depressive tendencies, Health data
We used three classifiers for the prediction. In addition, we used a combination of undersampling and bagging approach to improve predictive performances in our imbalanced data.
The finding was that we obtained recall of 0.65 from the logistic regression with L2 regularization. Moreover, some important questions for the prediction were included in DSM-5 or QIDS-SR, meaning that we found that not all main symptoms have been widely known.