Figure 4
From: Embracing noise to improve cross-batch prediction accuracy
Classifiers used by various settings. "A. Rank Values" is using rank values instead of absolute values of microarray data. "B. Bagging (10)" and "C. Bagging (100)" are using bagging of 10 and 100 bootstrap replicates respectively with rank values. "D. Dynamic Bagging" is using bagging with non-fixed number of bootstrap replicates where the number of bootstrap replicates is determined by the sequential hypothesis testing algorithm proposed in [14] and error rates set to be 10-4. "MIN" is the minimum number of classifiers used in all scenarios. "MAX" is the maximum number of classifiers used in all scenarios. "AVG" is the average number of classifiers used in all scenarios. The number of scenarios explored in each setting is 108.