Fig. 1From: Ensemble feature selection with data-driven thresholding for Alzheimer's disease biomarker discoveryA homogeneous feature selection ensemble. Sample1, Sample 2 … Sample n are randomly sampled subsets of the training data. The same feature selector is applied separately to each sample, generating n sets of selected features. An aggregator is applied to combine these feature sets into a single set, a threshold is applied and the resulting feature set is used as input to a survival model to assess its accuracyBack to article page