code: def __init__(
      self,
      name,
      construct,
      skip_methods=(),
      fit_args=make_classification(random_state=0),
  ):
      self.name = name
      self.construct = construct
      self.fit_args = fit_args
      self.skip_methods = skip_methods
  
imports: import functools
  from inspect import signature
  import numpy
  import pytest
  from sklearn.base import BaseEstimator, is_regressor
  from sklearn.datasets import make_classification
  from sklearn.ensemble import BaggingClassifier
  from sklearn.exceptions import NotFittedError
  from sklearn.feature_extraction.text import TfidfVectorizer
  from sklearn.feature_selection import RFE, RFECV
  from sklearn.linear_model import LogisticRegression, Ridge
  from sklearn.model_selection import GridSearchCV, RandomizedSearchCV
  from sklearn.pipeline import Pipeline, make_pipeline
  from sklearn.preprocessing import MaxAbsScaler, StandardScaler
  from sklearn.semi_supervised import SelfTrainingClassifier
  from sklearn.utils import all_estimators
  from sklearn.utils._testing import set_random_state
  from sklearn.utils.estimator_checks import _enforce_estimator_tags_X, _enforce_estimator_tags_y
  from sklearn.utils.validation import check_is_fitted
label_desc: Use image node_id 1 to create a new DelegatorData object  with example: obj = DelegatorData(name, construct, skip_methods, fit_args)