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Table 6 Mean difference in performance of similarity methods across MUV data sets.

From: Large scale study of multiple-molecule queries

Method AUC F1 BEDROC
MIN-RANK 0.054811 ± 0.007343 0.007274 ± 0.009481 0.011562 ± 0.013673
MAX-RANK 0.276475 ± 0.021613 0.139500 ± 0.023056 0.295164 ± 0.036878
SUM-RANK 0.187161 ± 0.021317 0.135635 ± 0.020176 0.251934 ± 0.029684
MAX-SIM 0.071096 ± 0.008692 0.000284 ± 0.005657 0.044583 ± 0.013589
MIN-SIM 0.252742 ± 0.020037 0.136318 ± 0.021634 0.286359 ± 0.031277
SUM-SIM 0.168871 ± 0.018754 0.104246 ± 0.014075 0.203296 ± 0.017032
NUMDEN-SIM 0.141477 ± 0.019134 0.096007 ± 0.014050 0.179707 ± 0.018725
BAYES 0.143037 ± 0.016147 0.115277 ± 0.014736 0.180010 ± 0.012881
BKD 0.001826 ± 0.001822 0.011572 ± 0.009888 0.002483 ± 0.005203
ETD --- 0.015242 ± 0.010510 ---
TPD 0.010170 ± 0.003688 0.004709 ± 0.007578 0.003758 ± 0.007367
SUM-EH 0.106459 ± 0.013059 0.056296 ± 0.007868 0.126204 ± 0.012854
SUM-ET 0.052051 ± 0.010111 0.001559 ± 0.004737 0.032111 ± 0.012709
SUM-TP 0.056095 ± 0.009880 --- 0.033664 ± 0.012780
  1. The mean difference in performance of similarity methods from that of the best method across the 17 MUV data sets. A confidence interval is provided with each measurement. All performances statistically indistinguishable (with a paired t-test yielding a p-value > 0.05) are listed in italics.