- shap.plots.beeswarm(shap_values, max_display=10, order=shap.Explanation.abs.mean(0), clustering=None, cluster_threshold=0.5, color=None, axis_color='#333333', alpha=1, show=True, log_scale=False, color_bar=True, plot_size='auto', color_bar_label='Feature value')
Create a SHAP beeswarm plot, colored by feature values when they are provided.
This is an
Explanationobject containing a matrix of SHAP values (# samples x # features).
How many top features to include in the plot (default is 10, or 7 for interaction plots).
matplotlib.pyplot.show()is called before returning. Setting this to
Falseallows the plot to be customized further after it has been created.
Whether to draw the color bar (legend).
- plot_size“auto” (default), float, (float, float), or None
What size to make the plot. By default, the size is auto-scaled based on the number of features that are being displayed. Passing a single float will cause each row to be that many inches high. Passing a pair of floats will scale the plot by that number of inches. If
Noneis passed, then the size of the current figure will be left unchanged.