I have a number of regression models from which I'm trying to choose the best performing one.
I have computed SSE, AIC and BIC for all, including distributions of errors from predictions on unseen data.
Any ideas on how to decide the best from this bunch based on these criteria? I understand these metrics should tell you the best performing model from the lowest values for each, but as seen in the table, the differences between a number of models are minimal. Apologies if the question is unclear or the solution obvious, Some of this is fairly foreign to me.