Nice article! Thanks for sharing! Could you explain better this part?

"All the models relying on the minimization of least squares (usual regressions, random forests with default parameters) are likely to perform poorly since they will return the mean over subsambles, while minimizing the absolute error returns the mean of the sample."

Why MAE represents mean of the sample and MSE the mean of subsamples? And why in the equation and code you used the median?

Great work pal