class_docstr: Custom early time series classifier. todo: write docstring.
  
  todo: describe your custom early time series classifier 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
class_docstr_tok: ["Custom","early","time","series","classifier",".","todo",":","write","docstring",".","todo",":","describe","your","custom","early","time","series","classifier","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: Fit early time series classifier to training data.
  
  core logic
  
  Parameters
  ----------
  X : Training data of type self.get_tag("X_inner_mtype")
  y : array-like, shape = [n_instances] - the class labels
  
  Returns
  -------
  self : reference to self.
  
  State change
  ------------
  creates fitted model (attributes ending in "_")
docstr_tok: ["Fit","early","time","series","classifier","to","training","data",".","core","logic","Parameters","--","--","--","--","--","X",":","Training","data","of","type","self.get_tag","(","``","X_inner_mtype","''",")","y",":","array-like",",","shape","=","[","n_instances","]","-","the","class","labels","Returns","--","--","--","-","self",":","reference","to","self",".","State","change","--","--","--","--","--","--","creates","fitted","model","(","attributes","ending","in","``","_","''",")"]
code: def _fit(self, X, y):
      """Fit early time series classifier to training data.
  
      core logic
  
      Parameters
      ----------
      X : Training data of type self.get_tag("X_inner_mtype")
      y : array-like, shape = [n_instances] - the class labels
  
      Returns
      -------
      self : reference to self.
  
      State change
      ------------
      creates fitted model (attributes ending in "_")
      """
  
file_path: sktime/extension_templates/early_classification.py
imports: from typing import Tuple
  import numpy
  from sktime.classification.early_classification import BaseEarlyClassifier
label_desc: Use image node_id 2 for calling the MyEarlyTimeSeriesClassifier obj's underlying member method code with example usage: obj._fit(X, y) without return types