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See sklearn repository when it comes to use cross validation source code a little look not to unders

Time:09-29

Concrete is:
In the parameters of the function calls using for input parameter value in the
scores=the parallel (
Of (_fit_and_score) (
Clone (estimator), X, y, scorers, train, test, verbose, None,
Fit_params return_train_score=return_train_score,
Return_times=True, return_estimator=return_estimator,
Error_score=error_score)
For train and test the in CV. The split (X, y, groups))


The parallel is the parallel instances, it is directly as a function call, is a function of, his parameter is introduced to a function, _fit_and_score is a function of the incoming
Question:
More than 1, behind a for in to train, test assignment, I want to know what is this principle,
2, why is a function of the parameters, the incoming _fit_and_score and its parameters to use "()" enclosed
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