Figure 6
From: To aggregate or not to aggregate high-dimensional classifiers
The cross-validation errors in different number of aggregation. In leukemia data, the misclassification rate keeps stable when the number of aggregating is more than 50. In grape data, the misclassification rate keeps stable when the number of aggregating is more than 100. In Gaucher data, the aggregating model is not stable.