When working with prediction problems, is there a need to consider the change in time or not?
For example, when trying to predict the price of a house, we just have the current features and the current price. The classification problem is to predict if the house price will be above a threshold or not. The regression problem is to predict the exact price.
Is there a need to have datasets with some time interval between them (for example X days or Y years) or we can predict with a dataset that was taken at a certain time? And in this case, is there a difference between classification and regression?