n_folds = 5
def rmsle(model):
kf = KFold(n_folds, shuffle=True, random_state=42).get_n_splits(train.values)
rmse = np.sqrt(-cross_val_score(model, train.values, y_train, scoring="neg_mean_squared_error", cv = kf))
return(rmse)
I’m new to kaggle, and got stuck in this code.
I found out that get_n_splits returns the number of split data batches.
Then, what is the difference of just using the code
n_folds = 5
def rmsle(model):
rmse = np.sqrt(-cross_val_score(model, train.values, y_train, scoring="neg_mean_squared_error", cv = 5))
return(rmse)
as above?
I know that there was a question which asked exactly the same thing, but I’m not a native English speaker so couldn’t understand it clearly.
Can someone give me a good reason for this?
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