docstr: Resets the predictor function or tree-based `sklearn` estimator.
  
  Parameters
  ----------
  predictor
      New predictor function or tree-based `sklearn` estimator.
docstr_tok: ["Resets","the","predictor","function","or","tree-based","`","sklearn","`","estimator",".","Parameters","--","--","--","--","--","predictor","New","predictor","function","or","tree-based","`","sklearn","`","estimator","."]
code: def reset_predictor(
      self,
      predictor: Union[
          Callable[[np.ndarray], np.ndarray], BaseEstimator
      ],
  ) -> None:
      """
      Resets the predictor function or tree-based `sklearn` estimator.
  
      Parameters
      ----------
      predictor
          New predictor function or tree-based `sklearn` estimator.
      """
      self.predictor = predictor
  
imports: import copy
  import logging
  import math
  import numbers
  import sys
  from abc import ABC, abstractmethod
  from enum import Enum
  from typing import Callable, Dict, Iterable, List, Optional, Tuple, Union, no_type_check
  import matplotlib.pyplot
  import numpy
  from scipy.stats.mstats import mquantiles
  from sklearn.base import BaseEstimator, is_classifier, is_regressor
  from sklearn.ensemble import RandomForestRegressor
  from sklearn.ensemble._gb import BaseGradientBoosting
  from sklearn.ensemble._hist_gradient_boosting.gradient_boosting import BaseHistGradientBoosting
  from sklearn.tree import DecisionTreeRegressor
  from sklearn.utils.extmath import cartesian
  from sklearn.utils.validation import check_is_fitted
  from tqdm import tqdm
  from alibi.api.defaults import DEFAULT_DATA_PD, DEFAULT_META_PD
  from alibi.api.interfaces import Explainer, Explanation
  from alibi.explainers.ale import get_quantiles
  from alibi.utils import _get_options_string
label_desc: Use image node_id 10 for calling the PartialDependenceBase obj's underlying member method code with example usage: obj.reset_predictor(predictor) without return types