| Data | Model | Normalization | None | Z-standard | Min-Max | MaxAbs (−1, 1) | Quantile Transform | Quantile Normalize |
| Wine Quality with binary target | Logistic | Total Loss | 0.038 | 0.058 | 0.100 | 0.166 | 0.062 | 0.038 |
| Bias | 0.037 | 0.036 | 0.037 | 0.047 | 0.034 | 0.037 | ||
| Variance | 0.000 | 0.022 | 0.063 | 0.144 | 0.028 | 0.001 | ||
| Noise | 0.000 | 0.000 | 0.000 | 0.024 | 0.000 | 0.000 | ||
| Variance-Bias Ratio | 0.010 | 0.609 | 1.710 | 3.086 | 0.809 | 0.022 | ||
| Percent Change from Raw | ~ | 153.636 | 265.145 | 440.891 | 165.508 | 100.728 | ||
| Decision Tree | ||||||||
| Total Loss | 0.061 | 0.772 | 0.696 | 0.684 | 0.688 | 0.061 | ||
| Bias | 0.030 | 0.608 | 0.491 | 0.475 | 0.481 | 0.030 | ||
| Variance | 0.031 | 0.164 | 0.205 | 0.046 | 0.207 | 0.031 | ||
| Noise | 0.000 | 0.000 | 0.000 | 0.162 | 0.000 | 0.000 | ||
| Variance-Bias Ratio | 1.033 | 0.269 | 0.417 | 0.098 | 0.430 | 1.034 | ||
| Percent Change from Raw | ~ | 1259.483 | 1135.652 | 1116.508 | 1123.095 | 100.079 | ||
| Random Forest | Total Loss | 0.039 | 0.822 | 0.762 | 0.754 | 0.749 | 0.039 | |
| Bias | 0.031 | 0.692 | 0.593 | 0.581 | 0.572 | 0.031 | ||
| Variance | 0.008 | 0.129 | 0.169 | 0.127 | 0.177 | 0.008 | ||
| Noise | 0.000 | 0.000 | 0.000 | 0.047 | 0.000 | 0.000 | ||
| Variance-Bias Ratio | 0.263 | 0.187 | 0.285 | 0.218 | 0.310 | 0.263 | ||
| Percent Change from Raw | ~ | 2087.923 | 1936.937 | 1916.597 | 1902.651 | 100.093 | ||
| SVM | Total Loss | 0.038 | 0.037 | 0.037 | 0.037 | 0.037 | 0.038 | |
| Bias | 0.035 | 0.037 | 0.037 | 0.037 | 0.037 | 0.035 | ||
| Variance | 0.003 | 0.000 | 0.000 | 0.000 | 0.000 | 0.003 |