code: def load(self, kwargs):
      # Naming parameter
      add_parameter(self, kwargs, "name", "ErrorCalculation")
      add_parameter(self, kwargs, "postprocessor_string", "")
  
      # Logging Parameters
      add_parameter(self, kwargs, "output_log", "outputs.csv")
      add_parameter(self, kwargs, "cost_functions", ["dice"])
      add_parameter(self, kwargs, "write_mode", "w")
      add_parameter(self, kwargs, "print_output", True)
  
      self.cost_function_dict = {
          "dice": dice_cost_function,
          "accuracy": accuracy_cost_function,
          "cluster_accuracy": cluster_accuracy_cost_function,
      }
  
      self.cost_function_label_dict = {
          "dice": "Dice Coeffecient",
          "accuracy": "Accuracy",
          "cluster_accuracy": "Cluster Accuracy",
      }
  
      self.transform_output = False
      self.csv_file = None
  
file_path: DeepNeuro/deepneuro/postprocessing/statistics.py
imports: import csv
  import numpy
  from skimage.measure import label
  from deepneuro.postprocessing.postprocessor import Postprocessor
  from deepneuro.utilities.util import add_parameter
label_desc: Use image node_id 1 for calling the ErrorCalculation obj's underlying member method code with example usage: obj.load(kwargs) without return types