I want to plot the roc curve for real time data(5 genes).
does with the roc curve can show which of these genes has more effect and more importance than others after drug treatment?
Hi,
ROC curves are frequently used to show in a graphical way the connection/trade-off between clinical sensitivity and specificity for every possible cut-off for a test or a combination of tests. In addition the area under the ROC curve gives an idea about the benefit of using the test(s) in question.
In a ROC curve the true positive rate (Sensitivity) is plotted in function of the false positive rate (100-Specificity) for different cut-off points of a parameter. ... The area under the ROC curve ( AUC ) is a measure of how well a parameter can distinguish between two diagnostic groups (diseased/normal).
The AUC is the area under the ROC curve. This score gives us a good idea of how well the model performances. As we see, the first model does quite a good job of distinguishing the positive and the negative values. Therefore, there the AUC score is 0.9 as the area under the ROC curve is large.
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