When you use nested estimators with grid search you can scope the parameters with __
as a separator. In this case the SVC model is stored as an attribute named estimator
inside the OneVsRestClassifier
model:
from sklearn.datasets import load_iris
from sklearn.multiclass import OneVsRestClassifier
from sklearn.svm import SVC
from sklearn.grid_search import GridSearchCV
from sklearn.metrics import f1_score
iris = load_iris()
model_to_set = OneVsRestClassifier(SVC(kernel="poly"))
parameters = {
"estimator__C": [1,2,4,8],
"estimator__kernel": ["poly","rbf"],
"estimator__degree":[1, 2, 3, 4],
}
model_tunning = GridSearchCV(model_to_set, param_grid=parameters,
score_func=f1_score)
model_tunning.fit(iris.data, iris.target)
print model_tunning.best_score_
print model_tunning.best_params_
That yields:
0.973290762737
{'estimator__kernel': 'poly', 'estimator__C': 1, 'estimator__degree': 2}