class_docstr: Defines MetadataRemovalRegressionModelWrapper, wrapping the
  regression model to ignore dropped feature metadata if any.
class_docstr_tok: ["Defines","MetadataRemovalRegressionModelWrapper",",","wrapping","the","regression","model","to","ignore","dropped","feature","metadata","if","any","."]
docstr: If needed, wraps the model to ignore the dropped features.
  
  :param model: The model or function to evaluate on the examples.
  :type model: function or model with a predict function
  :param dropped_features: List of features that were dropped by the
                           the user during training of their model.
  :type dropped_features: Optional[List[str]]
docstr_tok: ["If","needed",",","wraps","the","model","to","ignore","the","dropped","features",".",":","param","model",":","The","model","or","function","to","evaluate","on","the","examples",".",":","type","model",":","function","or","model","with","a","predict","function",":","param","dropped_features",":","List","of","features","that","were","dropped","by","the","the","user","during","training","of","their","model",".",":","type","dropped_features",":","Optional","[","List","[","str","]","]"]
code: def __init__(
      self, model: any, dropped_features: Optional[List[str]] = None
  ):
      """If needed, wraps the model to ignore the dropped features.
  
      :param model: The model or function to evaluate on the examples.
      :type model: function or model with a predict function
      :param dropped_features: List of features that were dropped by the
                               the user during training of their model.
      :type dropped_features: Optional[List[str]]
      """
      self.model = model
      self.dropped_features = dropped_features
  
imports: import json
  import warnings
  from pathlib import Path
  from typing import Any, List, Optional
  import jsonschema
  import pandas
  from erroranalysis._internal.constants import metric_to_display_name
  from erroranalysis._internal.error_analyzer import ModelAnalyzer
  from erroranalysis._internal.error_report import as_error_report
  from erroranalysis._internal.error_report import json_converter
  from raiutils.exceptions import UserConfigValidationException
  from raiutils.models import ModelTask
  from responsibleai._config.base_config import BaseConfig
  from responsibleai._interfaces import ErrorAnalysisData
  from responsibleai._internal.constants import ErrorAnalysisManagerKeys
  from responsibleai._internal.constants import FileFormats, ListProperties, ManagerNames
  from responsibleai._tools.shared.state_directory_management import DirectoryManager
  from responsibleai.exceptions import ConfigAndResultMismatchException, DuplicateManagerConfigException
  from responsibleai.managers.base_manager import BaseManager
  from responsibleai.utils import _find_features_having_missing_values, _measure_time
label_desc: Use image node_id 1 to create a new MetadataRemovalRegressionModelWrapper object  with example: obj = MetadataRemovalRegressionModelWrapper(model, dropped_features)