class_docstr: Abstract base class for time series regressors.
  
  The base regressor specifies the methods and method signatures that all
  regressors have to implement. Attributes with a underscore suffix are set in the
  method fit.
  
  Parameters
  ----------
  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.
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docstr: Magic * method, return concatenated RegressorPipeline, transformers on left.
  
  Overloaded multiplication operation for regressors. Implemented for `other`
  being a transformer, otherwise returns `NotImplemented`.
  
  Parameters
  ----------
  other: `sktime` transformer, must inherit from BaseTransformer
      otherwise, `NotImplemented` is returned
  
  Returns
  -------
  RegressorPipeline object, concatenation of `other` (first) with `self` (last).
docstr_tok: ["Magic","*","method",",","return","concatenated","RegressorPipeline",",","transformers","on","left",".","Overloaded","multiplication","operation","for","regressors",".","Implemented","for","`","other","`","being","a","transformer",",","otherwise","returns","`","NotImplemented","`",".","Parameters","--","--","--","--","--","other",":","`","sktime","`","transformer",",","must","inherit","from","BaseTransformer","otherwise",",","`","NotImplemented","`","is","returned","Returns","--","--","--","-","RegressorPipeline","object",",","concatenation","of","`","other","`","(","first",")","with","`","self","`","(","last",")","."]
code: def __rmul__(self, other):
      """Magic * method, return concatenated RegressorPipeline, transformers on left.
  
      Overloaded multiplication operation for regressors. Implemented for `other`
      being a transformer, otherwise returns `NotImplemented`.
  
      Parameters
      ----------
      other: `sktime` transformer, must inherit from BaseTransformer
          otherwise, `NotImplemented` is returned
  
      Returns
      -------
      RegressorPipeline object, concatenation of `other` (first) with `self` (last).
      """
      from sktime.regression.compose import RegressorPipeline
      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):
          # RegressorPipeline already has the dunder method defined
          if isinstance(self, RegressorPipeline):
              return other * self
          # if other is a TransformerPipeline but self is not, first unwrap it
          elif isinstance(other, TransformerPipeline):
              return RegressorPipeline(
                  regressor=self, transformers=other.steps
              )
          # if neither self nor other are a pipeline, construct a RegressorPipeline
          else:
              return RegressorPipeline(
                  regressor=self, transformers=[other]
              )
      elif is_sklearn_transformer(other):
          return TabularToSeriesAdaptor(other) * self
      else:
          return NotImplemented
  
file_path: sktime/sktime/regression/base.py
imports: import time
  import numpy
  from sktime.base import BasePanelMixin
  from sktime.datatypes import VectorizedDF
  from sktime.utils.sklearn import is_sklearn_transformer
  from sktime.utils.validation import check_n_jobs
label_desc: Use image node_id 2 for calling the BaseRegressor obj's underlying member method code with example usage: obj.__rmul__(other) and returns: unknown, unknown, NotImplemented, RegressorPipeline, RegressorPipeline