I have 20 independent variables(explanatory)and 1 dependent(respond) variable and I wish to use SVM as a regression problem to predict my dependent variable. but the point is that my independent(explanatory)variables are ranging differently.
e.g {x1 < 0} , {x2 > 0} , {-1
The question is that:
Am I allow to use these explanatory variables in my SVM Regression model without normalizing them? or I should normal them first and then use them to estimate my respond variable?
If I should normal them, is there any specific normalization formula?