SVM for different parameters in a for loop (a modelling question)
Hello, can rapidminer model my following problem?
I have a data and want to apply SVM. I need to see the behaviour of results on different parameters (epsilon, C and gamma).
Let say my C values will be 1,2,4 - gamma values 0.1, 0.2, 0.3, and epsilon values 0.1,0.2 . In this case i will have 3*3*2=18 models and want to write the predictions into an excel file. Is this possible in Rapidminer?
I dont need to optimize parameters so i dont need to use any validation or performance blocks. Also, my parameters will increase linearly or logarithmicly for ease.
Thanks in advance.
I have a data and want to apply SVM. I need to see the behaviour of results on different parameters (epsilon, C and gamma).
Let say my C values will be 1,2,4 - gamma values 0.1, 0.2, 0.3, and epsilon values 0.1,0.2 . In this case i will have 3*3*2=18 models and want to write the predictions into an excel file. Is this possible in Rapidminer?
I dont need to optimize parameters so i dont need to use any validation or performance blocks. Also, my parameters will increase linearly or logarithmicly for ease.
Thanks in advance.
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