def to_super(self):
if self.kernel == "linear":
superinstance = SVC(kernel="linear")
# superinstance.coef_ = self.coef_
else:
superinstance = SVC()
superinstance.C = self.C
superinstance._dual_coef_ = self._dual_coef_
superinstance._gamma = self._gamma
superinstance._impl = self._impl
superinstance._intercept_ = self._intercept_
superinstance._sparse = self._sparse
superinstance.cache_size = self.cache_size
superinstance.class_weight = self.class_weight
superinstance.class_weight_ = self.class_weight_
superinstance.classes_ = self.classes_
superinstance.coef0 = self.coef0
superinstance.decision_function_shape = self.decision_function_shape
superinstance.degree = self.degree
superinstance.dual_coef_ = self.dual_coef_
superinstance.epsilon = self.epsilon
superinstance.fit_status_ = self.fit_status_
superinstance.gamma = self.gamma
superinstance.intercept_ = self.intercept_
superinstance.kernel = self.kernel
superinstance.max_iter = self.max_iter
superinstance.n_support_ = self.n_support_
superinstance.nu = self.nu
superinstance.probA_ = self.probA_
superinstance.probB_ = self.probB_
superinstance.probability = self.probability
superinstance.random_state = self.random_state
superinstance.shape_fit_ = self.shape_fit_
superinstance.shrinking = self.shrinking
superinstance.support_ = self.support_
superinstance.support_vectors_ = self.support_vectors_
superinstance.tol = self.tol
superinstance.verbose = self.verbose
return superinstance
