code: def __init__(
      self,
      kernel,
      C,
      epsilon,
      tol,
      shrinking,
      gamma=0.1,
      degree=3,
      coef0=0.0,
      verbose=False,
      max_iter=-1,
      random_state=None,
  ):
      self.kernel = kernel
      self.C = C
      self.epsilon = epsilon
      self.tol = tol
      self.shrinking = shrinking
      self.degree = degree
      self.gamma = gamma
      self.coef0 = coef0
      self.verbose = verbose
      self.max_iter = max_iter
      self.random_state = random_state
      self.estimator = None
  
file_path: auto-sklearn/autosklearn/pipeline/components/regression/libsvm_svr.py
imports: from typing import Optional
  import resource
  import sys
  from ConfigSpace.conditions import EqualsCondition, InCondition
  from ConfigSpace.configuration_space import ConfigurationSpace
  from ConfigSpace.hyperparameters import CategoricalHyperparameter, UniformFloatHyperparameter, UniformIntegerHyperparameter, UnParametrizedHyperparameter
  from autosklearn.askl_typing import FEAT_TYPE_TYPE
  from autosklearn.pipeline.components.base import AutoSklearnRegressionAlgorithm
  from autosklearn.pipeline.constants import DENSE, PREDICTIONS, SPARSE, UNSIGNED_DATA
  from autosklearn.util.common import check_for_bool, check_none
label_desc: Use image node_id 1 to create a new LibSVM_SVR object from inherited base classes: AutoSklearnRegressionAlgorithm with example: obj = LibSVM_SVR(kernel, C, epsilon, tol, shrinking, gamma, degree, coef0, verbose, max_iter, random_state)