Sorry i will put in some context. I am stratifying because i am setting the sampling for splitting the data into validation and training data.
I have 5 catagorical variables, one is binary (target classifcation) and has a fairly even distribution of the two groups.
However the others have 4...
Hi all
I am wondering what the general rule is to stratify sampling in the data partion node?
for the catagorical variables
do you stratify by just the target variable?
or all input catagorical variables that have underepresented classes in them?
some advice would be greatly appreciated...
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