code: def findPrediction(row: pd.Series) -> Union[str, int, float]:
      """
      Make a prediction for a row of data frame on built gbm model
      Args:
          row (pd.Series): a row of a pandas data frame
      Returns:
          result (str or float): str for classifier, int or float
              for regressor
      """
      epoch = row["Epoch"]
      row = row.drop(labels=["Epoch"])
      columns = row.shape[0]
  
      params = []
      for j in range(0, columns - 1):
          params.append(row[j])
  
      module_name = f"outputs/rules/rules{epoch - 1}"
      myrules = load_module(module_name)
  
      # prediction = int(myrules.findDecision(params))
      prediction = myrules.findDecision(params)
  
      return prediction
  
file_path: chefboost/chefboost/tuning/gbm.py
imports: import gc
  from typing import Optional, Union
  import pandas
  import numpy
  from tqdm import tqdm
  from chefboost.commons import functions
  from chefboost.training import Training
  from chefboost.commons.logger import Logger
  from chefboost.commons.module import load_module
label_desc: Use image node_id 1 for calling a global function with example usage: findPrediction(row) and returns: prediction