class_docstr: Abstract base class for time series classifiers.
  
  The base classifier specifies the methods and method signatures that all
  classifiers have to implement. Attributes with an underscore suffix are set in the
  method fit.
  
  Parameters
  ----------
  classes_            : ndarray of class labels, possibly strings
  n_classes_          : integer, number of classes (length of classes_)
  fit_time_           : integer, time (in milliseconds) for fit to run.
  _class_dictionary   : dictionary mapping classes_ onto integers 0...n_classes_-1.
  _threads_to_use     : number of threads to use in fit as determined by n_jobs.
docstr: Magic * method, return concatenated ClassifierPipeline, transformers on left.
  
  Overloaded multiplication operation for classifiers. Implemented for `other`
  being a transformer, otherwise returns `NotImplemented`.
  
  Parameters
  ----------
  other: `sktime` transformer, must inherit from BaseTransformer
      otherwise, `NotImplemented` is returned
  
  Returns
  -------
  ClassifierPipeline object, concatenation of `other` (first) with `self` (last).
docstr_tok: ["Magic","*","method",",","return","concatenated","ClassifierPipeline",",","transformers","on","left",".","Overloaded","multiplication","operation","for","classifiers",".","Implemented","for","`","other","`","being","a","transformer",",","otherwise","returns","`","NotImplemented","`",".","Parameters","--","--","--","--","--","other",":","`","sktime","`","transformer",",","must","inherit","from","BaseTransformer","otherwise",",","`","NotImplemented","`","is","returned","Returns","--","--","--","-","ClassifierPipeline","object",",","concatenation","of","`","other","`","(","first",")","with","`","self","`","(","last",")","."]
code: def __rmul__(self, other):
      """Magic * method, return concatenated ClassifierPipeline, transformers on left.
  
      Overloaded multiplication operation for classifiers. Implemented for `other`
      being a transformer, otherwise returns `NotImplemented`.
  
      Parameters
      ----------
      other: `sktime` transformer, must inherit from BaseTransformer
          otherwise, `NotImplemented` is returned
  
      Returns
      -------
      ClassifierPipeline object, concatenation of `other` (first) with `self` (last).
      """
      from sktime.classification.compose import ClassifierPipeline
      from sktime.transformations.base import BaseTransformer
      from sktime.transformations.compose import TransformerPipeline
      from sktime.transformations.series.adapt import (
          TabularToSeriesAdaptor,
      )
  
      # behaviour is implemented only if other inherits from BaseTransformer
      #  in that case, distinctions arise from whether self or other is a pipeline
      #  todo: this can probably be simplified further with "zero length" pipelines
      if isinstance(other, BaseTransformer):
          # ClassifierPipeline already has the dunder method defined
          if isinstance(self, ClassifierPipeline):
              return other * self
          # if other is a TransformerPipeline but self is not, first unwrap it
          elif isinstance(other, TransformerPipeline):
              return ClassifierPipeline(
                  classifier=self, transformers=other.steps
              )
          # if neither self nor other are a pipeline, construct a ClassifierPipeline
          else:
              return ClassifierPipeline(
                  classifier=self, transformers=[other]
              )
      elif is_sklearn_transformer(other):
          return TabularToSeriesAdaptor(other) * self
      else:
          return NotImplemented
  
imports: import time
  import numpy
  from sktime.base import BasePanelMixin
  from sktime.datatypes import VectorizedDF, check_is_scitype, convert
  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 2 for calling the BaseClassifier obj's underlying member method code with example usage: obj.__rmul__(other) and returns: unknown, unknown, NotImplemented, ClassifierPipeline, ClassifierPipeline