Table 4 Performance comparison with different regressors on the training dataset.
From: Prediction of concrete compressive strength using a Deepforest-based model
Regressor | R2 | MSE | MAE | RMSE |
|---|---|---|---|---|
Linear | 0.56 | 123.63 | 8.91 | 11.11 |
KNeighbors | 0.75 | 69.83 | 6.31 | 8.35 |
DecisionTree | 0.82 | 49.74 | 4.72 | 7.04 |
SVR | 0.66 | 97.73 | 7.66 | 9.87 |
LASSO | 0.55 | 129.25 | 9.19 | 11.35 |
MLP | 0.42 | 162.49 | 10.23 | 12.74 |
ExtraTrees | 0.75 | 68.32 | 5.37 | 8.23 |
RandomForest | 0.90 | 28.00 | 3.71 | 5.26 |
AdaBoost | 0.78 | 61.21 | 6.35 | 7.80 |
GradientBoosting | 0.90 | 28.98 | 3.96 | 5.36 |
Bagging | 0.89 | 32.42 | 4.00 | 5.66 |
Deepforest | 0.91 | 26.32 | 3.60 | 5.11 |
