format_as_html(explanation, include_styles=True, force_weights=True, show=('method', 'description', 'transition_features', 'targets', 'feature_importances', 'decision_tree'), preserve_density=None, highlight_spaces=None, horizontal_layout=True, show_feature_values=False)[source]

Format explanation as html. Most styles are inline, but some are included separately in <style> tag, you can omit them by passing include_styles=False and call format_html_styles to render them separately (or just omit them). With force_weights=False, weights will not be displayed in a table for predictions where it is possible to show feature weights highlighted in the document. If highlight_spaces is None (default), spaces will be highlighted in feature names only if there are any spaces at the start or at the end of the feature. Setting it to True forces space highlighting, and setting it to False turns it off. If horizontal_layout is True (default), multiclass classifier weights are laid out horizontally. If show_feature_values is True, feature values are shown if present. Default is False.


Format hsl color as css color string.


Format just the styles, use with format_as_html(explanation, include_styles=False).


Max absolute feature for pos and neg weights.

remaining_weight_color_hsl(ws, weight_range, pos_neg)[source]

Color for “remaining” row. Handles a number of edge cases: if there are no weights in ws or weight_range is zero, assume the worst (most intensive positive or negative color).

render_targets_weighted_spans(targets, preserve_density)[source]

Return a list of rendered weighted spans for targets. Function must accept a list in order to select consistent weight ranges across all targets.

weight_color_hsl(weight, weight_range, min_lightness=0.8)[source]

Return HSL color components for given weight, where the max absolute weight is given by weight_range.


format_as_text(expl, show=('method', 'description', 'transition_features', 'targets', 'feature_importances', 'decision_tree'), highlight_spaces=None, show_feature_values=False)[source]

Format explanation as text.

  • expl (eli5.base.Explanation) – Explanation returned by eli5.explain_weights or eli5.explain_prediction functions.

  • 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.

  • show_feature_values (bool) – When True, feature values are shown along with feature contributions. Default is False.

  • 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).



Return a dictionary representing the explanation that can be JSON-encoded. It accepts parts of explanation (for example feature weights) as well.