verticapy.machine_learning.vertica.tsa.ensemble.TimeSeriesByCategory.features_importance#
- TimeSeriesByCategory.features_importance(idx: int = 0, show: bool = True, chart: PlottingBase | TableSample | Axes | mFigure | Highchart | Highstock | Figure | None = None, **style_kwargs) PlottingBase | TableSample | Axes | mFigure | Highchart | Highstock | Figure#
Computes the input submodel’s features importance.
Parameters#
- idx: int, optional
As the
TimeSeriesByCategorymodel generates multiple models, the importance of features varies for each submodel. Theidxparameter corresponds to the submodel index.- show: bool, optional
If set to
True, draw the feature’s importance.- chart: PlottingObject, optional
The chart object to plot on.
- **style_kwargs
Any optional parameter to pass to the Plotting functions.
Returns#
- obj
features importance.
Examples#
This model is built based on multiple base models. You should look at the source models to see entire examples.