code: def predict_proba(self, X):
      if isinstance(X, pd.Series):
          X = X.values.reshape(1, -1)
      if not isinstance(X, pd.DataFrame):
          X = pd.DataFrame(X, columns=self.feature_names)
      if self.ag_model.problem_type == REGRESSION:
          preds = self.ag_model.predict(X)
      else:
          preds = self.ag_model.predict_proba(X)
      if (
          self.ag_model.problem_type == REGRESSION
          or self.target_class is None
      ):
          return preds
      else:
          return preds[self.target_class]
  
file_path: autogluon/eda/src/autogluon/eda/analysis/explain.py
imports: import logging
  import warnings
  from typing import List, Optional
  import numpy
  import pandas
  import shap
  from autogluon.core.constants import BINARY, REGRESSION
  from autogluon.eda import AnalysisState
  from autogluon.eda.analysis.base import AbstractAnalysis
label_desc: Use image node_id 2 for calling the _ShapAutoGluonWrapper obj's underlying member method code with example usage: obj.predict_proba(X) and returns: preds, preds