code: def plot_y_scores(self) -> None:
      for group_name in self.bias_metrics_results.columns:
          if group_name == "female":
              continue
          group = self.p_groups[group_name]
          others = get_p_others(
              self.p_groups, group_name, self.privileged_race
          )
          group_title, others_title = self.get_titles(group_name)
          if self.y_scores is not None:
              plt.title(
                  "y_scores distribution by {group_label}/{others_label} classes".format(
                      group_label=group_title, others_label=others_title
                  )
              )
              bucket_count = 20
              bucket_size = 1 / bucket_count
              buckets = [
                  i * bucket_size for i in range(0, bucket_count)
              ]
              normalized_group_sizes = []
              normalized_others_sizes = []
              for bucket in buckets:
                  bucket_scores = (self.y_scores >= bucket) & (
                      self.y_scores < bucket + bucket_size
                  )
                  normalized_group_sizes.append(
                      bucket_scores.multiply(group).sum() / group.sum()
                  )
                  normalized_others_sizes.append(
                      bucket_scores.multiply(others).sum()
                      / others.sum()
                  )
              plt.bar(
                  x=np.array(buckets) + bucket_size / 2,
                  height=normalized_group_sizes,
                  label=group_title,
                  alpha=0.5,
                  width=bucket_size,
              )
              plt.bar(
                  x=np.array(buckets) + bucket_size / 2,
                  height=normalized_others_sizes,
                  label=others_title,
                  alpha=0.5,
                  width=bucket_size,
              )
              plt.legend()
              plt.xlabel("y_score")
              plt.ylabel("density")
              plt.show()
  
file_path: bias-detector/bias_detector/BiasReport.py
imports: import pandas
  import numpy
  from matplotlib import pyplot
  from bias_detector.BiasConfidence import BiasConfidence
  from bias_detector.BiasMetric import get_bias_metric_description, get_bias_metric, get_bias_metric_short_description
  from bias_detector.common import get_p_others, get_other_groups_names, races
label_desc: Use image node_id 4 for calling the BiasReport obj's underlying member method code with example usage: obj.plot_y_scores() without return types