class_docstr: Automagic anytime regressor.
  
  Parameters
  ----------
  refit : boolean, True
      Whether to refit the model on the full dataset (I think).
  
  random_state : random state, int or None (default=None)
      Random state or seed.
  
  verbose : integer, default=1
      Verbosity (higher is more output).
  
  type_hints : dict or None
          If dict, provide type information for columns.
          Keys are column names, values are types as provided by
          detect_types.
  
  shuffle : boolean, default=True
      Whether to shuffle the training set in cross-validation.
code: def __init__(
      self,
      refit=True,
      random_state=None,
      verbose=1,
      type_hints=None,
      shuffle=True,
  ):
      self.verbose = verbose
      self.refit = refit
      self.random_state = random_state
      self.type_hints = type_hints
      self.shuffle = shuffle
  
imports: from importlib.metadata import version
  import warnings
  import numpy
  import pandas
  import sklearn
  from sklearn.metrics import make_scorer, average_precision_score
  from sklearn.base import BaseEstimator, ClassifierMixin, RegressorMixin
  from sklearn.preprocessing import LabelEncoder
  from sklearn.utils.multiclass import type_of_target
  from sklearn.pipeline import make_pipeline, Pipeline
  from sklearn.exceptions import UndefinedMetricWarning
  from sklearn.model_selection import StratifiedKFold, KFold
  from sklearn.model_selection._validation import _fit_and_score
  from sklearn.utils.validation import check_is_fitted
  from dabl._available_if import available_if
  from sklearn.dummy import DummyClassifier
  from sklearn.experimental import enable_halving_search_cv
  from sklearn.model_selection import HalvingGridSearchCV
  from .preprocessing import EasyPreprocessor, detect_types
  from .pipelines import get_fast_classifiers, get_fast_regressors, get_any_classifiers
  from .utils import _validate_Xyt
label_desc: Use image node_id 1 to create a new SimpleRegressor object from inherited base classes: _BaseSimpleEstimator, RegressorMixin with example: obj = SimpleRegressor(refit, random_state, verbose, type_hints, shuffle)