Complete hazard ranking to analyze right-censored data: An ALS survival study
Fig 4
Feature adoption ratios in repeated cross-validation tests.
The adoption ratio of a feature is, when the models are allowed to take only a limited number of features, the ratio of models that selects the feature throughout all 20 rounds of cross-validation tests. Since the data were split randomly throughout all the tests, the models might pick up a different set of features. The most significant features were expected to have high adoption ratios. Features such as fvc, ALSFRS Total, and weight were adopted in all training process; features like fvc1, mouth and Q3_Swallowing were picked in more than half of the tests. (A) Feature adoption ratios when models were allowed to take 15 features at most. In total 22 features have been picked at least once. (B) Feature adoption ratios when models were allowed to take 6 features at most. In total 11 features have been taken at least once.