class_docstr: A label encoder that supports specifying a positive class on top of sklearn's LabelEncoder.
class_docstr_tok: ["A","label","encoder","that","supports","specifying","a","positive","class","on","top","of","sklearn","'s","LabelEncoder","."]
code: def __init__(self, positive_class=None):
      self.positive_class = positive_class
      self._le = LabelEncoder()
      self._mapping = None
      self._inverse_mapping = None
  
imports: import json
  import logging
  import re
  from typing import Any, Dict, List, Optional, Union
  import jsonschema
  import numpy
  import pandas
  from omegaconf import DictConfig, OmegaConf
  from sklearn.preprocessing import LabelEncoder
  from ..constants import AUTOMM, END_OFFSET, ENTITY_GROUP, NER_ANNOTATION, PROBABILITY, START_OFFSET
label_desc: Use image node_id 1 to create a new CustomLabelEncoder object  with example: obj = CustomLabelEncoder(positive_class)