class_docstr: Uncertainty Sampling based on Category Vector Inconsistency and Ranking of Scores [RCV18]_
  selects instances based on the inconsistency of predicted labels and per-class label rankings.
class_docstr_tok: ["Uncertainty","Sampling","based","on","Category","Vector","Inconsistency","and","Ranking","of","Scores","[","RCV18","]","_","selects","instances","based","on","the","inconsistency","of","predicted","labels","and","per-class","label","rankings","."]
docstr: Parameters
  ----------
  batch_size : int
      Batch size in which the computations are performed. Increasing the size increases
      the amount of memory used.
  prediction_threshold : float
      Confidence value above which a prediction counts as positive.
  epsilon : float
      A small value that is added to the argument of the logarithm to avoid taking the
      logarithm of zero.
  pbar : 'tqdm' or None, default='tqdm'
      Displays a progress bar if 'tqdm' is passed.
docstr_tok: ["Parameters","--","--","--","--","--","batch_size",":","int","Batch","size","in","which","the","computations","are","performed",".","Increasing","the","size","increases","the","amount","of","memory","used",".","prediction_threshold",":","float","Confidence","value","above","which","a","prediction","counts","as","positive",".","epsilon",":","float","A","small","value","that","is","added","to","the","argument","of","the","logarithm","to","avoid","taking","the","logarithm","of","zero",".","pbar",":","'tqdm","'","or","None",",","default='tqdm'","Displays","a","progress","bar","if","'tqdm","'","is","passed","."]
code: def __init__(
      self,
      batch_size=2048,
      prediction_threshold=0.5,
      epsilon=1e-8,
      pbar="tqdm",
  ):
      """
      Parameters
      ----------
      batch_size : int
          Batch size in which the computations are performed. Increasing the size increases
          the amount of memory used.
      prediction_threshold : float
          Confidence value above which a prediction counts as positive.
      epsilon : float
          A small value that is added to the argument of the logarithm to avoid taking the
          logarithm of zero.
      pbar : 'tqdm' or None, default='tqdm'
          Displays a progress bar if 'tqdm' is passed.
      """
      self.batch_size = batch_size
      self.prediction_threshold = prediction_threshold
      self.epsilon = epsilon
      self.pbar = pbar
  
file_path: small-text/small_text/query_strategies/multi_label.py
imports: import numpy
  from small_text.query_strategies.base import constraints
  from small_text.query_strategies.strategies import QueryStrategy
  from small_text.utils.context import build_pbar_context
label_desc: Use image node_id 1 to create a new CategoryVectorInconsistencyAndRanking object from inherited base classes: QueryStrategy with example: obj = CategoryVectorInconsistencyAndRanking(batch_size, prediction_threshold, epsilon, pbar)