PMC:4331676 / 29538-30366 JSONTXT

{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/4331676","sourcedb":"PMC","sourceid":"4331676","source_url":"https://www.ncbi.nlm.nih.gov/pmc/4331676","text":"Furthermore, to provide a graphic illustration to show the performance of the five protein representations, the corresponding ROC (receiver operating characteristic) curves were drawn in Figure 3, where the horizontal coordinate X is for the false positive rate or 1-SP and the vertical coordinate Y is for the true positive rate or SN. The best method would yield a point with the coordinate (0,1) meaning 0 false positive rate and 100% true positive rate. Therefore a perfect classification method would give a point with the coordinate (0,1) and a completely random guess would give a point along the diagonal from point (0,0) to (1,1). The area under the ROC curve called AUC is often used to indicate the performance quality of binary classification methods, where the larger the area, the better the predictive quality is.","tracks":[]}