class_docstr: Custom clusterer. todo: write docstring.
  
  todo: describe your custom clusterer here
  
  Hyper-parameters
  ----------------
  parama : int
      descriptive explanation of parama
  paramb : string, optional (default='default')
      descriptive explanation of paramb
  paramc : boolean, optional (default= whether paramb is not the default)
      descriptive explanation of paramc
  and so on
  
  Components
  ----------
  est : sktime.estimator, BaseEstimator descendant
      descriptive explanation of est
  est2: another estimator
      descriptive explanation of est2
  and so on
docstr: Predict the closest cluster each sample in X belongs to.
  
  Parameters
  ----------
  X : data to cluster based on model formed in _fit, of type self.get_tag(
  "X_inner_mtype")
  y: ignored, exists for API consistency reasons.
  
  Returns
  -------
  np.ndarray (1d array of shape (n_instances,))
      Index of the cluster each time series in X belongs to.
docstr_tok: ["Predict","the","closest","cluster","each","sample","in","X","belongs","to",".","Parameters","--","--","--","--","--","X",":","data","to","cluster","based","on","model","formed","in","_fit",",","of","type","self.get_tag","(","''","X_inner_mtype","''",")","y",":","ignored",",","exists","for","API","consistency","reasons",".","Returns","--","--","--","-","np.ndarray","(","1d","array","of","shape","(","n_instances",",",")",")","Index","of","the","cluster","each","time","series","in","X","belongs","to","."]
code: def _predict(self, X) -> np.ndarray:
      """Predict the closest cluster each sample in X belongs to.
  
      Parameters
      ----------
      X : data to cluster based on model formed in _fit, of type self.get_tag(
      "X_inner_mtype")
      y: ignored, exists for API consistency reasons.
  
      Returns
      -------
      np.ndarray (1d array of shape (n_instances,))
          Index of the cluster each time series in X belongs to.
      """
  
file_path: sktime/extension_templates/clustering.py
imports: import numpy
  from sktime.clustering import BaseClusterer
label_desc: Use image node_id 3 for calling the MyClusterer obj's underlying member method code with example usage: obj._predict(X) without return types