From: Predicting subjective well-being in a high-risk sample of Russian mental health app users
Classification | Threshold | N (Classes) | Features | Best model | F1-macro | F1-weighted | F1-low | F1-high | TruePositiveRate (low) | FalsePositiveRate (low) |
---|---|---|---|---|---|---|---|---|---|---|
binary | 0.51 | 221/151 | Words | AdaBoost | 0.56 | 0.581 | 0.669 | 0.452 | 0.697 | 0.57 |
RuLIWC | DecisionTree | 0.571 | 0.582 | 0.631 | 0.512 | 0.611 | 0.457 | |||
AppCats | AdaBoost | 0.58 | 0.602 | 0.694 | 0.466 | 0.738 | 0.57 | |||
Behavior | DecisionTree | 0.543 | 0.559 | 0.63 | 0.456 | 0.638 | 0.55 | |||
Clusters | RandomForest | 0.539 | 0.571 | 0.714 | 0.363 | 0.832 | 0.715 | |||
binary majority baseline | Â | Â | 0.378 | 0.456 | 0.373 | 0 | 1 | 1 | ||
trinary | 0.35/0.59 | 111/158/103 | Words | AdaBoost | 0.44 | 0.447 | 0.407 | 0.43 | 0.378 | 0.195 |
RuLIWC | AdaBoost | 0.381 | 0.399 | 0.413 | 0.238 | 0.405 | 0.241 | |||
AppCats | AdaBoost | 0.422 | 0.443 | 0.402 | 0.294 | 0.396 | 0.241 | |||
Behavior | AdaBoost | 0.425 | 0.438 | 0.427 | 0.329 | 0.414 | 0.23 | |||
Clusters | DecisionTree | 0.358 | 0.364 | 0.338 | 0.339 | 0.351 | 0.295 | |||
clusters + RuLIWC + Words | AdaBoost | 0.483 | 0.493 | 0.502 | 0.433 | 0.45 | 0.161 | |||
trinary majority baseline |  |  | 0.199 | 0.253 | – | – | 0 | 0 |