You can combine the columns which are need to be normalized into a vector by VectorAssembler and do normalization on it. Do another assembling for columns should not be normalized. At last, you can assemble the two vector into one vector as the feature column and feed it into model training.
Thanks Yanbo 2016-06-25 21:16 GMT-07:00 段石石 <burness1...@gmail.com>: > Hi all: > > > I use the MinMaxScaler for data normalization, but I found the the api > is only for Vector, we must vectorized the features firtst. However, the > feature usually include two parts: one is need to be Normalization, another > should not be normalized such as categorical. I want to add a api with the > DataFrame which aim to normalize the columns which we want to normalize. > And then we can make it to be vector and sent to the ML model api to train. > I think that will be very useful for the developer with machine learning. > > > > Best Regards > > Thanks >
