code: def __init__(
      self,
      C=1.0,
      kernel="rbf",
      degree=3,
      gamma="auto_deprecated",
      coef0=0.0,
      shrinking=True,
      probability=False,
      tol=1e-3,
      cache_size=200,
      class_weight=None,
      verbose=False,
      max_iter=-1,
      decision_function_shape="ovr",
      random_state=None,
  ):
      self.kernel = kernel
      self.degree = degree
      self.gamma = gamma
      self.coef0 = coef0
      self.tol = tol
      self.C = C
      self.shrinking = shrinking
      self.probability = probability
      self.cache_size = cache_size
      self.class_weight = class_weight
      self.verbose = verbose
      self.max_iter = max_iter
      self.decision_function_shape = decision_function_shape
      self.random_state = random_state
  
imports: import re
  from pprint import PrettyPrinter
  import numpy
  from sklearn.utils._pprint import _EstimatorPrettyPrinter
  from sklearn.linear_model import LogisticRegressionCV
  from sklearn.pipeline import make_pipeline
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.feature_selection import SelectKBest, chi2
  from sklearn import config_context
label_desc: Use image node_id 1 to create a new SVC object from inherited base classes: BaseEstimator with example: obj = SVC(C, kernel, degree, gamma, coef0, shrinking, probability, tol, cache_size, class_weight, verbose, max_iter, decision_function_shape, random_state)