From: Data reduction techniques for highly imbalanced medicare Big Data
Features classifier | 10 | 15 | 20 | 25 | 30 | 80 |
---|---|---|---|---|---|---|
CatBoost | 0.6600 | 0.6850 | 0.7143 | 0.7047 | 0.7023 | 0.6812 |
ET | 0.0233 | 0.0261 | 0.0317 | 0.0429 | 0.0358 | 0.0336 |
LightGBM | 0.5756 | 0.5904 | 0.6185 | 0.6009 | 0.6030 | 0.5766 |
Logistic regression | 0.0076 | 0.0205 | 0.0217 | 0.0074 | 0.0076 | 0.0099 |
Random forest | 0.2820 | 0.2758 | 0.3168 | 0.3225 | 0.2990 | 0.2017 |
XGBoost | 0.6436 | 0.6535 | 0.6798 | 0.6708 | 0.6681 | 0.6536 |