| Random Forest | Total Loss | 0.408 | 0.459 | 0.408 | 0.408 | 0.408 | 0.408 | |
| Bias | 0.380 | 0.459 | 0.380 | 0.380 | 0.380 | 0.380 | ||
| Variance | 0.028 | 0.000 | 0.028 | 0.028 | 0.028 | 0.028 | ||
| Noise | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | ||
| Bias-Variance Ratio | 0.074 | 0.000 | 0.074 | 0.074 | 0.074 | 0.074 | ||
| Percent Change from Raw | ~ | 112.494 | 100.000 | 100.000 | 100.000 | 99.989 | ||
| SVM | Total Loss | 0.457 | 0.459 | 0.457 | 0.457 | 0.457 | 0.457 | |
| Bias | 0.454 | 0.459 | 0.455 | 0.454 | 0.455 | 0.455 | ||
| Variance | 0.003 | 0.000 | 0.002 | 0.002 | 0.002 | 0.003 | ||
| Noise | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | ||
| Bias-Variance Ratio | 0.006 | 0.000 | 0.005 | 0.005 | 0.005 | 0.006 | ||
| Percent Change from Raw | ~ | 100.520 | 100.094 | 100.000 | 100.094 | 100.018 | ||
| Gradient Boosting | Total Loss | 0.475 | 0.495 | 0.474 | 0.475 | 0.475 | 0.474 | |
| Bias | 0.386 | 0.452 | 0.386 | 0.386 | 0.386 | 0.386 | ||
| Variance | 0.089 | 0.043 | 0.089 | 0.089 | 0.089 | 0.089 | ||
| Noise | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | ||
| Bias-Variance Ratio | 0.230 | 0.095 | 0.230 | 0.230 | 0.230 | 0.230 | ||
| Percent Change from Raw | ~ | 104.234 | 99.950 | 100.000 | 100.019 | 99.971 | ||
| Neural Network | Total Loss | 0.376 | 0.459 | 0.382 | 0.376 | 0.380 | 0.376 | |
| Bias | 0.346 | 0.454 | 0.343 | 0.346 | 0.343 | 0.346 | ||
| Variance | 0.030 | 0.006 | 0.039 | 0.039 | 0.037 | 0.030 | ||
| Noise | 0.000 | 0.000 | 0.000 | 0.009 | 0.000 | 0.000 | ||
| Bias-Variance Ratio | 0.087 | 0.012 | 0.114 | 0.114 | 0.107 | 0.087 | ||
| Percent Change from Raw | ~ | 122.285 | 101.825 | 100.017 | 101.063 | 100.011 |