Visualise deweather model feature importance — plot_dw

Visualise the feature importance (% Gain for boosted tree models) for each variable of a deweather model, with some customisation.

Usage

plot_dw_importance(dw, aggregate_factors = FALSE, sort = TRUE, cols = "tol")

dw: A deweather model created with build_dw_model().
aggregate_factors: Defaults to FALSE. If TRUE, the importance of factor inputs (e.g., Weekday) will be summed into a single variable. This only applies to certain engines which report factor importance as disaggregate features.
sort: If TRUE, the default, features will be sorted by their importance. If FALSE, they will be sorted alphabetically. In plot_dw_importance() this will change the ordering of the y-axis, whereas in get_dw_importance() it will change whether var is returned as a factor or character data type.
cols: Colours to use for plotting. See openair::openColours().

a ggplot2 figure