Using the sklearn.grid_search.GridSearchCV class, perform a grid search of the polynomial order hyperparameter space with cross-validation and report the performance on an independent test set. code example
Example: Exhaustive search over specified parameter values for an estimator
from sklearn import svm, datasets
from sklearn.model_selection import GridSearchCV
iris = datasets.load_iris()
parameters = {'kernel':('linear', 'rbf'), 'C':[1, 10]}
svc = svm.SVC()
clf = GridSearchCV(svc, parameters)
clf.fit(iris.data, iris.target)
sorted(clf.cv_results_.keys())