class_docstr: Abstract base class for time series clusterer.
  
  Parameters
  ----------
  n_clusters: int, defaults = None
      Number of clusters for model.
class_docstr_tok: ["Abstract","base","class","for","time","series","clusterer",".","Parameters","--","--","--","--","--","n_clusters",":","int",",","defaults","=","None","Number","of","clusters","for","model","."]
code: def __init__(self, n_clusters: int = None):
      self.fit_time_ = 0
      self._class_dictionary = {}
      self._threads_to_use = 1
      self.n_clusters = n_clusters
      super().__init__()
      _check_estimator_deps(self)
  
imports: import time
  from typing import Any, Union
  import numpy
  import pandas
  from sktime.base import BaseEstimator
  from sktime.datatypes import check_is_scitype, convert_to, scitype_to_mtype
  from sktime.utils.sklearn import is_sklearn_transformer
  from sktime.utils.validation import check_n_jobs
  from sktime.utils.validation._dependencies import _check_estimator_deps
label_desc: Use image node_id 1 to create a new BaseClusterer object from inherited base classes: BaseEstimator with example: obj = BaseClusterer(n_clusters)