Summarizes variable importance in a mrIML model at both a global
(across all the response models) and local (for individual response models) level.
This can be done for a plain mrIML model or bootstrap results obtained from
mrBootstrap().
Usage
mrVip(
mrIMLobj,
mrBootstrap_obj = NULL,
threshold = 0.1,
global_top_var = 10,
local_top_var = 5,
taxa = NULL,
model_perf = NULL
)Arguments
- mrIMLobj
A list object output by
mrIMLpredicts().- mrBootstrap_obj
A list of bootstrap results output by
mrBootstrap().- threshold
The performance threshold for response models (AUC for classification and R2 for regression). Only response models that meet this performance criterion are plotted.
- global_top_var
The number of top global variables to display (default: 10).
- local_top_var
The number of top local variables for each response to display (default: 5).
- taxa
A character string identifying which response model should be plotted.
- model_perf
A list object containing model performance metrics output by
mrIMLperformance(). If not supplied, thenmrIMLperformance()is run insidemrvip()to get performance metrics.
Value
A list containing:
$vi_data: Variable importance data in its raw form (including bootstrap samples ifmrBootstrap_objwas supplied).$vi_tbl: Variable importance data point estimates.$vi_plot: A grouped plot of the most important variables both globally and for the individual response models.
Examples
# Without bootstrap
mrIML_rf <- mrIML::mrIML_bird_parasites_RF
vip_results <-mrVip(mrIML_rf, taxa = "Plas")
# With bootstrap
# \donttest{
mrIML_rf_boot <- mrIML_rf %>%
mrBootstrap(num_bootstrap = 5)
#>
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mrIML_rf_vip <- mrVip(
mrIML_rf,
mrBootstrap_obj = mrIML_rf_boot
)
# }