> For example, in Advances in Financial Machine Learning, the author discusses how to pick sensible thresholds and transform the data to convert the regression

> For example, in Advances in Financial Machine Learning, the author discusses how to pick sensible thresholds and transform the data to convert the regression into a classification problem. This is interesting! Standard wisdom says that you get more statistical power from predicting a continuous variable as such, and then applying a threshold on the output, rather than trying to model the classification directly. Modeling the dichotomisation directly is equivalent to throwing a third of the data in the rubbish bin: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2972292/#__sec16title https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2972292/#__sec1...