import optunity
import optunity.metrics
import sklearn.svm
@optunity.cross_validated(x=X_train, y=y_train, num_folds=10, num_iter=2)
def svm_auc(x_train, y_train, x_test, y_test, logC, logGamma):
model = sklearn.svm.SVC(C=10 logC, gamma=10 logGamma).fit(x_train, y_train)
decision_values = model.decision_function(x_test)
return optunity.metrics.roc_auc(y_test, decision_values)
hps, , = optunity.maximize(svm_auc, num_evals=200, logC=[-5, 2], logGamma=[-5, 1]).any()
optimal_model = sklearn.svm.SVC(C=10 hps['logC'], gamma=10 hps['logGamma']).fit(X_train, y_train)