While studying data mining methods I have come to understand that there are two main categories:
- Association rules
Since I want to predict the user availability (output) based on location, activity, battery level(input for the training model) I think it's obvious that I would choose "Predictive methods" but now I can't seem to choose between classification and regression. From what I understand this far, classification can solve my problem because the output is "available" or "not available".
First question is: can classification provide me with the probability/likelihood of the user being available or not available?
As in the output wouldn't just be 0(not available) or 1 (for available) but it's be something like:
- 80% available
- 20% not available
Second question is, can this problem also be solved using regression?
I get that regression is used for continuous output (not just 0 or 1 outputs) but can't the output be the continuous value of the user availability? like the output being 80 meaning user is 80% available (implicitly the user is 20% unavailable)