docstr: Creates a FairGBM model.
  
  The FairGBM model is a novel method of InProcessing, where a boosting trees
  algorithm (LightGBM) is subject to pre-defined fairness constraints.
  
  Parameters
  ----------
  **kwargs : dict, optional
      A dictionary containing the hyperparameters for the FairGBM model.
code: def __init__(self, **kwargs):
      """Creates a FairGBM model.
  
      The FairGBM model is a novel method of InProcessing, where a boosting trees
      algorithm (LightGBM) is subject to pre-defined fairness constraints.
  
      Parameters
      ----------
      **kwargs : dict, optional
          A dictionary containing the hyperparameters for the FairGBM model.
      """
      self.logger = create_logger("methods.inprocessing.FairGBM")
      self.model = FairGBMClassifier(**kwargs)
      self.logger.debug(
          f"Instantiating FairGBM with following kwargs: {kwargs}"
      )
  
file_path: aequitas/src/aequitas/fairflow/methods/inprocessing/fairgbm.py
imports: from typing import Optional
  import pandas
  from fairgbm import FairGBMClassifier
  from ...utils import create_logger
  from .inprocessing import InProcessing
label_desc: Use image node_id 1 to create a new FairGBM object from inherited base classes: InProcessing with example: obj = FairGBM()