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. 2017 Feb 2;9:7. doi: 10.1186/s13321-016-0189-4

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© The Author(s) 2017

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Fig. 1 — Illustration of the relation between cutoff χ and number of predicted actives/non-actives. Assuming a list of compounds ranked according to their predicted activity values, all compounds that are located on the left side of χ on this ranked list are predicted to be active, while all compounds that are located on the right-hand side of χ on this list are predicted to be non-active. All compounds that fall along the left-hand side of χ define the ‘selection set’; in this example this includes five compounds. The total number of compounds in the selection set is N _s (here: 5), while the total number of compounds in the entire collection is N (here: 15). The number of true actives in the selection set is n _s (here: 3) and the number of true actives in the entire data collection is n (here: 4). Using these abbreviations, one can define the number of true positives TP as being equal to n _s, the number of true negatives TN equal to (N − N _s − n + n _s), the number of false positives FP equal to (N _s − n _s), and the number of false negatives FN being equal to (n − n _s)