I am attempting to predict a binomial outcome based on a set of continuous and binomial predictors in a time-series. Eg.
Y/N buy car ~ cost +Y/N get loan + future gas price predictions
If I was trying to take the output of a classifier and a regression equation based on the same training dataset and come up with whether or not to buy a car for a specific case, is there any reason a classification algorithm would be better or worse than regression?
This seems to provide a general rule of thumb, but I would really like a highly specific answer eg. “Classification algorithms do this better because…”
- Does either approach work better for time-series data?
- Does either approach handle erratic data better?