class_docstr: A pool-based active learner in which a pool holds all available unlabeled data.
  
  It uses a classifier, a query strategy and manages the mutually exclusive partition over the
  whole training data into labeled and unlabeled.
  
  Parameters
  ----------
  clf_factory : small_text.classifiers.factories.AbstractClassifierFactory
      A factory responsible for creating new classifier instances.
  query_strategy : small_text.query_strategies.QueryStrategy
      Query strategy which is responsible for selecting instances during a `query()` call.
  dataset : ~small_text.data.datasets.Dataset
      A training dataset that is supported by the underlying classifier.
  reuse_model : bool, default=False
      Reuses the previous model during retraining (if a previous model exists),
      otherwise creates a new model for each retraining.
  
  Attributes
  ----------
  indices_labeled : numpy.ndarray
      Indices of instances (relative to `self.x_train`) constituting the labeled pool.
  indices_ignored : numpy.ndarray or scipy.sparse.csr_matrix
      Indices of instances (relative to `self.x_train`) which have been ignored,
      i.e. which will never be returned by a query.
  y : numpy.ndarray or scipy.sparse.csr_matrix
      Labels for the the current labeled pool. Each tuple `(x_indices_labeled[i], y[i])`
      represents one labeled sample.
  indices_queried : numpy.ndarray or None
      Queried indices returned by the last `query()` call, or `None` if no query has been
      executed yet.
  fit_kwargs : dict
      Keyword arguments that will be passed to the `fit()` call during `update()`.
code: def query_strategy(self):
      return self._query_strategy
  
imports: import numpy
  from abc import ABC, abstractmethod
  from pathlib import Path
  from scipy.sparse import csr_matrix
  from small_text.base import LABEL_IGNORED
  from small_text.exceptions import LearnerNotInitializedException
  from small_text.utils.data import list_length
  from small_text.utils.labels import concatenate, get_ignored_labels_mask, remove_by_index
  from small_text.version import __version__
label_desc: Use image node_id 13 for calling the PoolBasedActiveLearner obj's underlying member method code with example usage: obj.query_strategy() and returns: self