lightgbm.plot_importance
- lightgbm.plot_importance(booster, ax=None, height=0.2, xlim=None, ylim=None, title='Feature importance', xlabel='Feature importance', ylabel='Features', importance_type='auto', max_num_features=None, ignore_zero=True, figsize=None, dpi=None, grid=True, precision=3, **kwargs)[source]
Plot model’s feature importances.
- Parameters:
booster (Booster or LGBMModel) – Booster or LGBMModel instance which feature importance should be plotted.
ax (matplotlib.axes.Axes or None, optional (default=None)) – Target axes instance. If None, new figure and axes will be created.
height (float, optional (default=0.2)) – Bar height, passed to
ax.barh()
.xlim (tuple of 2 elements or None, optional (default=None)) – Tuple passed to
ax.xlim()
.ylim (tuple of 2 elements or None, optional (default=None)) – Tuple passed to
ax.ylim()
.title (str or None, optional (default="Feature importance")) – Axes title. If None, title is disabled.
xlabel (str or None, optional (default="Feature importance")) – X-axis title label. If None, title is disabled. @importance_type@ placeholder can be used, and it will be replaced with the value of
importance_type
parameter.ylabel (str or None, optional (default="Features")) – Y-axis title label. If None, title is disabled.
importance_type (str, optional (default="auto")) – How the importance is calculated. If “auto”, if
booster
parameter is LGBMModel,booster.importance_type
attribute is used; “split” otherwise. If “split”, result contains numbers of times the feature is used in a model. If “gain”, result contains total gains of splits which use the feature.max_num_features (int or None, optional (default=None)) – Max number of top features displayed on plot. If None or <1, all features will be displayed.
ignore_zero (bool, optional (default=True)) – Whether to ignore features with zero importance.
figsize (tuple of 2 elements or None, optional (default=None)) – Figure size.
dpi (int or None, optional (default=None)) – Resolution of the figure.
grid (bool, optional (default=True)) – Whether to add a grid for axes.
precision (int or None, optional (default=3)) – Used to restrict the display of floating point values to a certain precision.
**kwargs – Other parameters passed to
ax.barh()
.
- Returns:
ax – The plot with model’s feature importances.
- Return type:
matplotlib.axes.Axes