Hi Kristina,
The input column of StandardScaler must be vector type, because it's
usually used as feature scaling before model training and the type of
feature column should be vector in most cases.
If you only want to standardize a numeric column, you can wrap it as a
vector and feed into
Hi,
The code below gives me an unexpected result. I expected that
StandardScaler (in ml, not mllib) will take a specified column of an input
dataframe and subtract the mean of the column and divide the difference by
the standard deviation of the dataframe column.
However, Spark gives me the
