Choose Predictive Models
I have a classification Problem with binary target attribute. All other Atrributes are numerical. In the Rapidminer are about 80 Operators, which can be used for classification. It is nearly impossible to try all of them...
I found the ROC as a tool to choose the Operator to use. I just dont unterstand how it works and how it can provide a "perfect" Model for my Problem. For example if i put 10 Operators in the compare ROC Operator they are all with standard settings in there. The result are curves and the curve which comes the closest to the top left is the best and therefore this Operator ist the best. But what is when i change the Parameters from the 10 Operators? Then i get a total different ROC. So its just try and error right?
Is there any Method to find the best Operator for my Problem? Or does it all come down to use one Operator within the optimize Parameters and find so the best Operator with the best accuracy?
I hope i explained my question well...