class_docstr: BalancedBinningReference generates a histogram with vertical lines
  showing the recommended value point to bin your data so they can be evenly
  distributed in each bin.
  
  Parameters
  ----------
  ax : matplotlib Axes, default: None
      This is inherited from FeatureVisualizer and is defined within
      ``BalancedBinningReference``.
  
  target : string, default: "y"
      The name of the ``y`` variable
  
  bins : number of bins to generate the histogram, default: 4
  
  kwargs : dict
      Keyword arguments that are passed to the base class and may influence
      the visualization as defined in other Visualizers.
  
  Attributes
  ----------
  bin_edges_ : binning reference values
  
  Examples
  --------
  >>> visualizer = BalancedBinningReference()
  >>> visualizer.fit(y)
  >>> visualizer.show()
  
  
  Notes
  -----
  These parameters can be influenced later on in the visualization
  process, but can and should be set as early as possible.
code: def __init__(self, ax=None, target=None, bins=4, **kwargs):
      super(BalancedBinningReference, self).__init__(ax, **kwargs)
  
      self.target = target
      self.bins = bins
  
file_path: yellowbrick/yellowbrick/target/binning.py
imports: import numpy
  from yellowbrick.target.base import TargetVisualizer
  from yellowbrick.exceptions import YellowbrickValueError
label_desc: Use image node_id 1 to create a new BalancedBinningReference object from inherited base classes: TargetVisualizer with example: obj = BalancedBinningReference(ax, target, bins)