Having completed an interesting course on Linear Regression on coursera, one aspect was never addressed that I am curious about in terms of best approach.
With reference to the classic house price prediction use case:
What is the best approach therefore?
Do we keep on updating the input replacing older house prices of yesteryear?
Or do we add an extra feature for Date of Sale - include a temporal aspect as a feature? I mention this as it was never discussed, but at the same time it seems so obvious. Inclusion of such an attrbue means it may get a weight, etc.
I can think of a few things but am more interested in the expert opinion.