plot_imp: plot feature importance

In easyalluvial: Generate Alluvial Plots with a Single Line of Code

plot feature importance

Description

plot important features of model response alluvial as bars

Usage

plot_imp(p, data_input, truncate_at = 50, color = "darkgrey")

Arguments

p	alluvial plot
data_input	dataframe used to generate alluvial plot
truncate_at	integer, limit number of features to that value, Default: 50
color	character vector, Default: 'darkgrey'

Value

ggplot object

Examples

## Not run: 
df = mtcars2[, ! names(mtcars2) %in% 'ids' ]

train = caret::train( disp ~ .
                     , df
                     , method = 'rf'
                     , trControl = caret::trainControl( method = 'none' )
                     , importance = TRUE )

pred_train = caret::predict.train(train, df)

p = alluvial_model_response_caret(train, degree = 3, pred_train = pred_train)

plot_imp(p, mtcars2)


## End(Not run)

easyalluvial documentation built on May 29, 2024, 5:32 a.m.