Hands-On Ensemble Learning with R

Complementary statistical tests

Here, a model is selected over another plausible one. The accuracy of one model seems higher than the other. The area under curve (AUC) of the ROC of a model is greater than that of another. However, it is not appropriate to base the conclusion on pure numbers only. It is important to conclude whether the numbers hold significance from the point of view of statistical inference. In the analytical world, it is pivotal that we make use of statistical tests whenever they are available to validate claims/hypotheses. A reason for using statistical tests is that probability can be highly counterintuitive, and what appears on the surface might not be the case upon closer inspection, after incorporating the chance variation. ...