This is not really a MATLAB question, but it does show confusion about how to use a specific toolbox. Anyway, I think you are approaching this from the wrong end of the horse. And we all know what comes from the wrong end of a horse. :)
You don't use a curve fitting tool to classify data. You use a curve fitting tool when you have a model that you want to fit to some data.
So first, you need to postulate some model. Then you can fit the model to some data. At the end, you may decide if the model fit poorly. If it exhibits lack of fit, etc. Then you might return to the initial step, and see if you can think of a better model.
In general, it is best if physical principles can be used to postulate the model. That makes it more likely the model might fit well.
For example, suppose I had some population data. Single species, bacteria growing in a petri dish. I might then postulate an exponential growth rate curve. THEN use a curve fitting tool to fit the model.
But, suppose I see the population does not grow continuously, but it stops after a while, or crashes? Now we might decide the model simply does not fit the data. In fact, more complex models, probably models that are derived from the solution to a valid ODE would be good. Fit that model next.