plot feature importance
plot important features of model response alluvial as bars
plot_imp(p, data_input, truncate_at = 50, color = "darkgrey")
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' |
ggplot object
## 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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.