class_docstr: Aggregation function for multiple metrics.
class_docstr_tok: ["Aggregation","function","for","multiple","metrics","."]
docstr: Specifies what value should be used to replace the missing value.
  
  :returns: The replacement value for the missing value.
  :rtype: (int, list, list, list, list, int)
docstr_tok: ["Specifies","what","value","should","be","used","to","replace","the","missing","value",".",":","returns",":","The","replacement","value","for","the","missing","value",".",":","rtype",":","(","int",",","list",",","list",",","list",",","list",",","int",")"]
code: def _fill_na_value(self):
      """Specifies what value should be used to replace the missing value.
  
      :returns: The replacement value for the missing value.
      :rtype: (int, list, list, list, list, int)
      """
      zero_array = [0]
      if self.num_labels > 2:
          zero_array = zero_array * self.num_labels
      return (0, zero_array, zero_array, zero_array, zero_array, 0)
  
imports: import logging
  import math
  import warnings
  from abc import ABC, abstractmethod
  import numpy
  import pandas
  from sklearn.metrics import multilabel_confusion_matrix
  from erroranalysis._internal.cohort_filter import filter_from_cohort
  from erroranalysis._internal.constants import DIFF, PRED_Y, ROW_INDEX, TRUE_Y, MatrixParams, MetricKeys, Metrics, ModelTask, metric_to_display_name
  from erroranalysis._internal.metrics import get_ordered_classes, is_multi_agg_metric, metric_to_func
  from raiutils.exceptions import UserConfigValidationException
label_desc: Use image node_id 5 for calling the _MultiMetricAggFunc obj's underlying member method code with example usage: obj._fill_na_value() and returns: int,  zero_array,  zero_array,  zero_array,  zero_array,  int