class_docstr: Manages issues related to imbalance class examples.
  
  Parameters
  ----------
  datalab:
      The Datalab instance that this issue manager searches for issues in.
  
  threshold:
      Minimum fraction of samples of each class that are present in a dataset without class imbalance.
code: def collect_info(self, class_name: str, labels: np.ndarray) -> dict:
      params_dict = {
          "threshold": self.threshold,
          "Rarest Class": class_name,
          "given_label": labels,
      }
      info_dict = {**params_dict}
      return info_dict
  
file_path: cleanlab/cleanlab/datalab/internal/issue_manager/imbalance.py
imports: from __future__ import annotations
  from typing import TYPE_CHECKING, ClassVar
  import numpy
  import pandas
  from cleanlab.datalab.internal.issue_manager import IssueManager
label_desc: Use image node_id 3 for calling the ClassImbalanceIssueManager obj's underlying member method code with example usage: obj.collect_info(class_name, labels) and returns: info_dict