# datatable.models.Ftrl.feature_importances¶

feature_importances

Feature importances as calculated during the model training and normalized to [0; 1]. The normalization is done by dividing the accumulated feature importances over the maximum value.

## Parameters¶

return
Frame

A frame with two columns: feature_name that has stype str32, and feature_importance that has stype float32 or float64 depending on whether the .double_precision option is False or True.