You may also find VectorSlicer and SQLTransformer useful in your case. Just
out of curiosity, how would you typically handles categorical features,
except for OneHotEncoder.
Regards,
Yuhao
2016-07-01 4:00 GMT-07:00 Yanbo Liang :
> You can combine the columns which are need to be normalized into
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.
Thank
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
