Table 4 Predictive performance of machine learning regression algorithms for dataset 1 and dataset 2
From: Machine learning hyperparameter selection for Contrast Limited Adaptive Histogram Equalization
Dataset | Algorithms | Clip limit | Number of tiles | ||
|---|---|---|---|---|---|
RMSE | R 2 | RMSE | R 2 | ||
Dataset 1 | CART | 0.04 | 0.70 | 0.12 | 0.15 |
MLP | 0.03 | 0.85 | 0.11 | 0.24 | |
SVM | 0.04 | 0.85 | 0.10 | 0.27 | |
RF | 0.03 | 0.86 | 0.11 | 0.25 | |
XGBoost | 0.01 | 0.93 | 0.13 | 0.22 | |
Dataset 2 | CART | 0.04 | 0.63 | 0.17 | 0.09 |
MLP | 0.05 | 0.56 | 0.16 | 0.14 | |
SVM | 0.04 | 0.61 | 0.17 | 0.15 | |
RF | 0.03 | 0.76 | 0.14 | 0.37 | |
XGBoost | 0.03 | 0.76 | 0.14 | 0.35 | |