code: def plot_feature_importance(self):
      fi = pd.DataFrame(index=self.model.feature_names_)
      fi["importance"] = self.model.feature_importances_
  
      fi.loc[fi["importance"] > 0.1].sort_values("importance").plot(
          kind="barh", figsize=(16, 9), title="Feature Importance"
      )
  
      plt.show()
  
imports: import os
  from typing import Optional
  import numpy
  import pandas
  from catboost import CatBoostClassifier, CatBoostRegressor, Pool
  from matplotlib import pyplot
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.operations.evaluation.operation_implementations.implementation_interfaces import ModelImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.core.utils import default_fedot_data_dir
label_desc: Use image node_id 5 for calling the FedotCatBoostClassificationImplementation obj's underlying member method code with example usage: obj.plot_feature_importance() without return types