code: def get_log_likelihood_ratio(
      p_pos: float,
      p_feature: float,
      p_pos_feature: float,
      total_count: int,
  ) -> float:
      """
      Returns the Log likelihood ratio of a feature, a correlation
      and statistical test that gives the probability of correctly predicting
      the label in ratio to probability of incorrectly predicting the label.
      https://en.wikipedia.org/wiki/Likelihood_function#Likelihood_ratio
  
      :param p_pos: The probability of the positive outcome in the dataset.
      :type p_pos: float
      :param p_feature: The probability of the feature in the dataset.
      :type p_feature: float
      :param p_pos_feature: The probability of the positive outcome and the
          feature in the dataset.
      :type p_pos_feature: float
      :param total_count: The total number of observations in the dataset.
      :type total_count: int
      :return: The Log likelihood ratio of the feature.
      :rtype: float
      """
      return (
          -np.inf
          if p_pos_feature == 0
          else np.log(p_pos_feature / p_pos)
      )
  
imports: import itertools
  import warnings
  from typing import Callable, Dict, List, Tuple
  import numpy
  import pandas
  import scipy
  from responsibleai.databalanceanalysis.balance_measures import BalanceMeasures
  from responsibleai.databalanceanalysis.constants import Constants, Measures
label_desc: Use image node_id 6 for calling a global function with example usage: get_log_likelihood_ratio(p_pos, p_feature, p_pos_feature, total_count) and returns: unknown