Plotting & Export¶

Visualize a fitted SGT, or export it to other formats.

plot_tree¶

sgtlearn.plot_tree(estimator, *, X=None, max_depth=None, feature_names=None, class_names=None, label='feature', impurity=False, proportion=False, precision=2, cmap=('#E8A0BF', '#FAC898', '#B3CDE3', '#CCEBC5', '#DECBE4', '#FED9A6', '#FFFFCC', '#E5D8BD'), ax=None, fontsize=None, node_aspect_ratio=2.5, n_hist_bins=20)[source]¶

Render a fitted SGT estimator with matplotlib (see module docstring).

Parameters:

estimator (Any)
max_depth (int | None)
feature_names (list[str] | None)
class_names (list[str] | bool | None)
label (str)
impurity (bool)
proportion (bool)
precision (int)
cmap (Any)
ax (Axes | None)
fontsize (int | None)
node_aspect_ratio (float)
n_hist_bins (int)

Return type:

list[Any]

export_graphviz¶

sgtlearn.export_graphviz()[source]¶

Serialize the fitted tree as Graphviz DOT (not implemented).

Return type:: None

export_text¶

sgtlearn.export_text()[source]¶

Return a human-readable multiline description of the tree (not implemented).

Return type:: None