Question 2: Can you inform if all the 12 attributes are read as numerical type (Integer or real or numeric) into the studio and also if the problem you are trying to solve is classification or regression? The process I built is for classification.
You can make some modifications based on your data and you can also post the errors you are getting here for more understanding.
Did you create the sub-process inside "Optimize parameter (evolutionary)"?
If not, you should have a sub-process with your required model and performance inside this operator. I attached a .rmp file in this thread for your reference. Please look at the subprocess by double-clicking the Optimize parameter evolutionary operator. I used cross-validation, you can use split or any other validation your need inside this to reduce run time.
If you observe the edit parameter list, I selected "C" to be optimized for SVM. You can select whatever you need based on your requirements.
To see the attached process in your Rapidminer, download this and in your rapidminer studio go to FILE --> Import Process and navigate to the downloaded process (.rmp file).
Note: You can only select the range when you use the optimize parameter (evolutionary operator). If you want to try specific values, you can use "Optimize parameter (Grid)".
Please let us know if you need more information.