code: def inverse_transform(
      self, preds: np.ndarray, threshold: float = 0.5
  ) -> List[List[str]]:
      data = []
      for sample in preds:
          x = []
          for label_x in np.where(sample >= threshold)[0]:
              x.append(self.idx2vocab[label_x])
          data.append(x)
      return data
  
file_path: Kashgari/kashgari/utils/multi_label.py
imports: from typing import List, Dict
  import numpy
  from kashgari.types import MultiLabelClassificationLabelVar
label_desc: Use image node_id 4 for calling the MultiLabelBinarizer obj's underlying member method code with example usage: obj.inverse_transform(preds, threshold) and returns: data