Question: What can be the maximum depth of a ( binary ) decision tree built on a training data with n samples and p features? Here

What can be the maximum depth of a

(

binary

)

decision tree built on a training data with n samples and p features? Here "binary" means that we only divide each node into two children nodes. Further, assume the n samples are all unique

(

.

.,

the n

-

-

p data matrix has no duplicate rows

) .

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