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