View source: R/variable_importance.R
plot.variable_importance | R Documentation |
Plot variable importance
## S3 method for class 'variable_importance' plot( x, title = "model", max_char = 40, caption = NULL, font_size = 11, point_size = 3, print = TRUE, ... )
x |
A data frame from |
title |
Either "model", "none", or a string to be used as the plot caption. "model" puts the name of the best-performing model, on which variable importances are generated, in the title. |
max_char |
Maximum length of variable names to leave untruncated.
Default = 40; use |
caption |
Plot title |
font_size |
Relative size for all fonts, default = 11 |
point_size |
Size of dots, default = 3 |
print |
Print the plot? |
... |
Unused |
A ggplot object, invisibly.
machine_learn(pima_diabetes[1:50, ], patient_id, outcome = diabetes, tune = FALSE) %>% get_variable_importance() %>% plot()
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