Hello @slevin Lee
This is the intended behaviour, and it is due to the structure of these modules.
In “__init__.py” file of ‘sklearn’ library, you will find that it is importing several submodules and functions to be available directly from ‘sklearn’ namespace. Where as ‘gplearn’ library does not expose anything at top level when imported. It is related with how packages defined in there their ‘__init__.py’ file.
Added advantage of many properties get imported with ‘sklearn’ can be seen in below example. Let’s say you want to use ‘clone’ function of ‘sklearn’ then consider below scenarios:
1. Without importing submodules, functions at Top level:
from sklearn.base import clone
2. With importing submodules, functions at Top level:
from sklearn import clone
