code: def __init__(
      self,
      eval_metric: str | Scorer = None,
      time_limit: float = None,
      presets: List[str] | str = None,
      hyperparameters: dict | str = None,
      path: str = None,
      verbosity: int = 2,
      init_args: dict = None,
      fit_args: dict = None,
  ):
      self.eval_metric = eval_metric
      self.time_limit = time_limit
      self.presets = presets
      self.hyperparameters = hyperparameters
      self.path = path
      self.verbosity = verbosity
      self.init_args = init_args
      self.fit_args = fit_args
  
file_path: autogluon/tabular/src/autogluon/tabular/experimental/_tabular_regressor.py
imports: from __future__ import annotations
  from typing import List
  import pandas
  from sklearn.base import BaseEstimator, RegressorMixin
  from sklearn.utils.validation import check_array, check_is_fitted, check_X_y
  from autogluon.core.metrics import Scorer
  from ..None import TabularPredictor
  from ._scikit_mixin import ScikitMixin
label_desc: Use image node_id 1 to create a new TabularRegressor object from inherited base classes: BaseEstimator, RegressorMixin, ScikitMixin with example: obj = TabularRegressor(eval_metric, time_limit, presets, hyperparameters, path, verbosity, init_args, fit_args)