Most of my latest articles revolved round understanding how positive a mannequin is about its predictions. If we all know the uncertainty of predictions, we will make well-informed choices. I confirmed you ways we will use Conformal Prediction to quantify a mannequin’s uncertainty. I wrote about Conformal Prediction approaches for classification and regression issues.
For these approaches, we assume that the order of remark doesn’t matter, i.e., that our information is exchangeable. That is cheap for classification and regression issues. Nonetheless, the belief doesn’t maintain for time sequence issues. Right here, the order of observations typically incorporates vital info, equivalent to traits…