plot_shap_waterfall
method plot_shap_waterfall(models=None, rows=0, show=None, target=1, title=None, legend=None, figsize=None, filename=None, display=True)[source]
Plot SHAP's waterfall plot.
The SHAP value of a feature represents the impact of the
evidence provided by that feature on the model's output. The
waterfall plot is designed to visually display how the SHAP
values (evidence) of each feature move the model output from
our prior expectation under the background data distribution,
to the final model prediction given the evidence of all the
features. Features are sorted by the magnitude of their SHAP
values with the smallest magnitude features grouped together
at the bottom of the plot when the number of features in the
models exceeds the show
parameter. Read more about SHAP plots
in the user guide.
Parameters |
models: int, str, Model or None, default=None
Model to plot. If None, all models are selected. Note that
leaving the default option could raise an exception if there
are multiple models. To avoid this, call the plot directly
from a model, e.g.,
rows: int or str, default=0atom.lr.plot_shap_waterfall() .
Selection of rows to plot. The
plot_shap_waterfall method does not support plotting
multiple samples.
show: int or None, default=None
Number of features (ordered by importance) to show. If
None, it shows all features.
target: int, str or tuple, default=1
Class in the target column to target. For multioutput tasks,
the value should be a tuple of the form (column, class).
Note that for binary and multilabel tasks, the selected
class is always the positive one.
title: str, dict or None, default=None
Title for the plot.
legend: str, dict or None, default=None
Do nothing. Implemented for continuity of the API.
figsize: tuple or None, default=None
Figure's size in pixels, format as (x, y). If None, it
adapts the size to the number of features shown.
filename: str, Path or None, default=None
Save the plot using this name. Use "auto" for automatic
naming. The type of the file depends on the provided name
(.html, .png, .pdf, etc...). If
display: bool or None, default=Truefilename has no file type,
the plot is saved as png. If None, the plot is not saved.
Whether to render the plot. If None, it returns the figure.
|
Returns | {#plot_shap_waterfall-plt.Figure or None}
plt.Figure or None
Plot object. Only returned if display=None .
|
See Also
Plot SHAP's bar plot.
Plot SHAP's beeswarm plot.
Plot SHAP's heatmap plot.
Example
>>> from atom import ATOMClassifier
>>> from sklearn.datasets import load_breast_cancer
>>> X, y = load_breast_cancer(return_X_y=True, as_frame=True)
>>> atom = ATOMClassifier(X, y, random_state=1)
>>> atom.run("LR")
>>> atom.plot_shap_waterfall(show=10)