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. 2018 Jun 27;1(2):275–282. doi: 10.1093/jamiaopen/ooy021

Table 1.

Area under the learning curve (ALC) and number of training examples required to reach target area under the ROC curve (AUC) of the uncertainty, representative, and combined query strategies evaluated on the substance interactions and clinical medicine datasets

Type Query strategy Substance interactions
Clinical medicine
ALC |L| @ 0.80 AUC ALC |L| @ 0.80 AUC
Baseline Passive 0.590 1295 0.491 2473
SM 0.597 1218 0.541 2093
Uncertainty LC 0.606 1051 0.543 2043
LCB2 0.607 1060 0.542 2089
D2C 0.623 891 0.548 2166
Representative Density 0.622 905 0.547 2136
Min-Max 0.634 657 0.550 2127
Combined ID (β = 0.01) 0.626 771 0.534 2157
ID (β =1) 0.642 546 0.542 2146
ID (β = 100) 0.635 653 0.550 2174
ID (dynamic β)a 0.641 587 0.549 2180

Bold values indicate the best performing method for that metric.

a

Novel algorithm.