Hello friends: I'm doing a predictive model for predicting a numeric variable and intend to use an artificial neural network. In KNIME, model variables must be between 0 and 1. As I have some categorical variables, some other nominal and ordinal, I would like to know what the best strategy to transform the data of the latter variables. I plan to use the One2Many Node, but some times, depending of classes of nominal feature, the number of new features tends to grow a lot. The other way is to treat the categories as if they were numeric codes and then normalize [ 0,1]. Can anyone give me any advice on how I proceed? Thank you

Gabriel

CHILE