Open Peter9192 opened 2 years ago
We've been talking about nested cross-validation. Scikit-learn actually has a nice example of this. In essence, it looks like this:
inner_cv = KFold(n_splits=4, shuffle=True, random_state=i) outer_cv = KFold(n_splits=4, shuffle=True, random_state=i) clf = GridSearchCV(estimator=svm, param_grid=p_grid, cv=inner_cv) # Note that the gridsearch instance is passed into the outer cv score = cross_val_score(clf, X=X_iris, y=y_iris, cv=outer_cv).mean()
It would be nice if we could eventually do the same, but for that we need to make sure our model/pipeline can work with xarray data structures.
related to AI4S2S/s2spy#71 AI4S2S/lilio#46
We've been talking about nested cross-validation. Scikit-learn actually has a nice example of this. In essence, it looks like this:
It would be nice if we could eventually do the same, but for that we need to make sure our model/pipeline can work with xarray data structures.
related to AI4S2S/s2spy#71 AI4S2S/lilio#46