![]() ![]() Set shuffle=True in the KFold class to conduct shuffling. IID datasets should be shuffled when assigned to folds. Since each observation is presumed to have been independently generated, KFCV begins with the premise that the data is independent and identically distributed (IID).When you perform KFCV, there are three things you need to keep in mind: For example, if your computer has four cores (which is common in laptops), scikit-learn will utilize all four cores simultaneously to speed up the procedure. Finally, n_jobs=-1 instructs scikit-learn to employ every available core.The scoring parameter defines our success measure.K-fold is by far the most popular, although there are others, such as leave-one-out cross-validation, in which the number of folds k matches the number of observations. Our cross-validation approach is determined by the cv parameter.X and y: The dataset inputs and outputs. ![]()
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