Table 3.
95% confidence intervals for accuracy results (presented in Table 2) for distinguishing between recurrent low grade gliomas which transformed to a higher grade and those that did not using five classifiers trained on HRMAS features selected using three feature selection methods.
| Accuracy | Features | LDA | Logistic | FT | SVM | Boosting |
|---|---|---|---|---|---|---|
| Training | Chi-square Gain ratio Conditional |
0.82–0.98 0.72–0.93 0.84–0.99 |
0.93–1 0.93–1.00 0.93–1.00 |
0.84–0.99 0.84–0.99 0.82–0.99 |
0.84–0.99 0.84–0.99 0.84–0.99 |
0.93–1.00 0.93–1.00 0.90–1.00 |
| Cross-valid | Chi-square Gain ratio Conditional |
0.84–0.99 0.82–0.98 0.90–1.00 |
0.84–0.99 0.87–1.00 0.79–0.97 |
0.79–0.97 0.79–0.97 0.82–0.98 |
0.84–0.99 0.82–0.98 0.84–0.99 |
0.87–1.00 0.84–0.99 0.79–0.97 |
| Bootstrap | Chi-square Gain ratio Conditional |
0.86–0.88 0.83–0.85 0.88–0.90 |
0.95–0.97 0.95–0.97 0.94–0.96 |
0.88–0.90 0.88–0.90 0.88–0.90 |
0.84–0.86 0.82–0.84 0.82–0.84 |
0.95–0.97 0.93–0.95 0.93–0.95 |
| ROC AUC | Chi-square Gain ratio Conditional |
0.88–1.00 0.96–1.00 1.00–1.00 |
0.82–0.98 1.00–1.00 0.96–1.00 |
0.89–1 1.00–1.00 1.00–1.00 |
0.85–0.99 1.00–1.00 0.96–1.00 |
0.88–1.00 1.00–1.00 0.93–1.00 |
| Precision | Chi-square Gain ratio Conditional |
0.78–0.98 0.89–1.00 0.89–1.00 |
0.78–0.98 0.89–1.00 0.89–1.00 |
0.74–0.98 0.89–1.00 0.89–1.00 |
0.78–0.98 0.89–1.00 0.89–1.00 |
0.74–0.98 0.89–1.00 0.89–1.00 |
| Recall | Chi-square Gain ratio Conditional |
0.71–0.99 0.85–1.00 0.85–1.00 |
0.77–0.99 0.85–1.00 0.85–1.00 |
0.71–0.97 0.85–1.00 0.85–1.00 |
0.77–0.99 0.85–1.00 0.85–1.00 |
0.71–0.97 0.85–1.00 0.85–1.00 |
| F measure | Chi-square Gain ratio Conditional |
0.75–0.99 0.87–1.00 0.87–1.00 |
0.78–0.99 0.87–1.00 0.87–1.00 |
0.72–0.98 0.87–1.00 0.87–1.00 |
0.78–0.99 0.87–1.00 0.87–1.00 |
0.72–0.98 0.87–1.00 0.87–1.00 |