docs: def show_weights(estimator, **kwargs):
      """ Return an explanation of estimator parameters (weights)
      as an IPython.display.HTML object. Use this function
      to show classifier weights in IPython.
  
      :func:`show_weights` accepts all
      :func:`eli5.explain_weights` arguments and all
      :func:`eli5.formatters.html.format_as_html`
      keyword arguments, so it is possible to get explanation and
      customize formatting in a single call.
  
      Parameters
      ----------
      estimator : object
          Estimator instance. This argument must be positional.
  
      top : int or (int, int) tuple, optional
          Number of features to show. When ``top`` is int, ``top`` features with
          a highest absolute values are shown. When it is (pos, neg) tuple,
          no more than ``pos`` positive features and no more than ``neg``
          negative features is shown. ``None`` value means no limit.
  
          This argument may be supported or not, depending on estimator type.
  
      target_names : list[str] or {'old_name': 'new_name'} dict, optional
          Names of targets or classes. This argument can be used to provide
          human-readable class/target names for estimators which don't expose
          clss names themselves. It can be also used to rename estimator-provided
          classes before displaying them.
  
          This argument may be supported or not, depending on estimator type.
  
      targets : list, optional
          Order of class/target names to show. This argument can be also used
          to show information only for a subset of classes. It should be a list
          of class / target names which match either names provided by
          an estimator or names defined in ``target_names`` parameter.
  
          This argument may be supported or not, depending on estimator type.
  
      feature_names : list, optional
          A list of feature names. It allows to specify feature
          names when they are not provided by an estimator object.
  
          This argument may be supported or not, depending on estimator type.
  
      feature_re : str, optional
          Only feature names which match ``feature_re`` regex are shown
          (more precisely, ``re.search(feature_re, x)`` is checked).
  
      feature_filter : Callable[[str], bool], optional
          Only feature names for which ``feature_filter`` function returns True
          are shown.
  
      show : List[str], optional
          List of sections to show. Allowed values:
  
          * 'targets' - per-target feature weights;
          * 'transition_features' - transition features of a CRF model;
          * 'feature_importances' - feature importances of a decision tree or
            an ensemble-based estimator;
          * 'decision_tree' - decision tree in a graphical form;
          * 'method' - a string with explanation method;
          * 'description' - description of explanation method and its caveats.
  
          ``eli5.formatters.fields`` provides constants that cover common cases:
          ``INFO`` (method and description), ``WEIGHTS`` (all the rest),
          and ``ALL`` (all).
  
      horizontal_layout : bool
          When True, feature weight tables are printed horizontally
          (left to right); when False, feature weight tables are printed
          vertically (top to down). Default is True.
  
      highlight_spaces : bool or None, optional
          Whether to highlight spaces in feature names. This is useful if
          you work with text and have ngram features which may include spaces
          at left or right. Default is None, meaning that the value used
          is set automatically based on vectorizer and feature values.
  
      include_styles : bool
          Most styles are inline, but some are included separately in <style> tag;
          you can omit them by passing ``include_styles=False``. Default is True.
  
      **kwargs: dict
          Keyword arguments. All keyword arguments are passed to
          concrete explain_weights... implementations.
  
      Returns
      -------
      IPython.display.HTML
          The result is printed in IPython notebook as an HTML widget.
          If you need to display several explanations as an output of a single
          cell, or if you want to display it from a function then use
          IPython.display.display::
  
              from IPython.display import display
              display(eli5.show_weights(clf1))
              display(eli5.show_weights(clf2))
  
      """
      format_kwargs, explain_kwargs = _split_kwargs(kwargs)
      expl = explain_weights(estimator, **explain_kwargs)
      html = format_as_html(expl, **format_kwargs)
      return HTML(html)