code: def __init__(
      self,
      C,
      nu,
      epsilon,
      kernel="rbf",
      *,
      degree,
      gamma,
      coef0,
      tol,
      shrinking,
      cache_size,
      max_iter,
      tau,
      class_weight,
      decision_function_shape,
      break_ties,
      algorithm,
      svm_type=None,
      **kwargs,
  ):
      self.C = C
      self.nu = nu
      self.epsilon = epsilon
      self.kernel = kernel
      self.degree = degree
      self.coef0 = coef0
      self.gamma = gamma
      self.tol = tol
      self.shrinking = shrinking
      self.cache_size = cache_size
      self.max_iter = max_iter
      self.tau = tau
      self.class_weight = class_weight
      self.decision_function_shape = decision_function_shape
      self.break_ties = break_ties
      self.algorithm = algorithm
      self.svm_type = svm_type
  
imports: from abc import ABCMeta, abstractmethod
  from enum import Enum
  from numbers import Number, Real
  import numpy
  from scipy import sparse
  from sklearn.base import BaseEstimator
  from daal4py.sklearn._utils import sklearn_check_version
  from onedal import _backend
  from ..common._estimator_checks import _check_is_fitted
  from ..common._mixin import ClassifierMixin, RegressorMixin
  from ..common._policy import _get_policy
  from ..datatypes import from_table, to_table
  from ..utils import _check_array, _check_n_features, _check_X_y, _column_or_1d, _validate_targets
label_desc: Use image node_id 1 to create a new BaseSVM object from inherited base classes: BaseEstimator with example: obj = BaseSVM(C, nu, epsilon, kernel)