This is an example about how to perform gridsearch with SVM.
>>> from sklearn import svm, grid_search, datasets
>>> iris = datasets.load_iris()
>>> parameters = {'kernel':('linear', 'rbf'), 'C':[1, 10]}
>>> svr = svm.SVC()
>>> clf = grid_search.GridSearchCV(svr, parameters)
>>> clf.fit(iris.data, iris.target)
I have the following two questions:
1. If I set cv=6, will k-fold automatically be selected? If not, how to I
set it?
2. How do I specify that the best estimator parameters should be average
of the output from the k folds, or is it done by default?
Thank you,
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