Re: Machine Learning and census models
On reflection, I suspect that if the aim is extrapolation into the future a more principled alternative to function approximation with leave-one-out cross-validation might be a variation where the in sample data for each run consists only of the data preceding the out of sample data point. (The reason is that as fitting intermediate points is easier, it could easily lead to overfitting).
Has anyone any views on this rather important general situation?
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