class_docstr: Abstract class for explainability results of a :class:`_ForecastingModelExplainer`.
  The subclasses should implement convenient access to explanations.
class_docstr_tok: ["Abstract","class","for","explainability","results","of","a",":","class",":","`","_ForecastingModelExplainer","`",".","The","subclasses","should","implement","convenient","access","to","explanations","."]
docstr: Returns one or multiple explanations based on some input parameters.
docstr_tok: ["Returns","one","or","multiple","explanations","based","on","some","input","parameters","."]
code: def get_explanation(self, *args, **kwargs):
      """Returns one or multiple explanations based on some input parameters."""
      pass
  
imports: from abc import ABC, abstractmethod
  from typing import Any, Dict, List, Optional, Union
  import pandas
  import shap
  from darts import TimeSeries
  from darts.logging import get_logger, raise_if, raise_if_not, raise_log
label_desc: Use image node_id 1 for calling the _ExplainabilityResult obj's underlying member method code with example usage: obj.get_explanation() without return types