Table 7 Test results of training set samples.
From: Machine learning detection of manipulative environmental disclosures in corporate reports
Panel A. Comparison of SMOTE forecast performance metrics | |||
|---|---|---|---|
Logistic regression (LR) | Decision Trees (DT) | Random Forest (RF) | |
Accuracy | 0.5437 | 0.7373 | 0.8368 |
F1-Score | 0.48 | 0.79 | 0.85 |
AUC Value | 0.5437 | 0.7373 | 0.8368 |
Panel B. Comparison of ADASYN forecast performance metrics | |||
|---|---|---|---|
Logistic regression (LR) | Decision trees (DT) | Random Forest (RF) | |
Accuracy | 0.5099 | 0.6669 | 0.7409 |
F1-Score | 0.45 | 0.65 | 0.75 |
AUC Value | 0.51 | 0.6669 | 0.7408 |
