plot.nn {radiant.model} | R Documentation |
Plot method for the nn function
Description
Plot method for the nn function
Usage
## S3 method for class 'nn'
plot(
x,
plots = "vip",
size = 12,
pad_x = 0.9,
nrobs = -1,
incl = NULL,
incl_int = NULL,
shiny = FALSE,
custom = FALSE,
...
)
Arguments
x |
Return value from |
plots |
Plots to produce for the specified Neural Network model. Use "" to avoid showing any plots (default). Options are "olden" or "garson" for importance plots, or "net" to depict the network structure |
size |
Font size used |
pad_x |
Padding for explanatory variable labels in the network plot. Default value is 0.9, smaller numbers (e.g., 0.5) increase the amount of padding |
nrobs |
Number of data points to show in dashboard scatter plots (-1 for all) |
incl |
Which variables to include in a coefficient plot or PDP plot |
incl_int |
Which interactions to investigate in PDP plots |
shiny |
Did the function call originate inside a shiny app |
custom |
Logical (TRUE, FALSE) to indicate if ggplot object (or list of ggplot objects) should be returned. This option can be used to customize plots (e.g., add a title, change x and y labels, etc.). See examples and https://ggplot2.tidyverse.org for options. |
... |
further arguments passed to or from other methods |
Details
See https://radiant-rstats.github.io/docs/model/nn.html for an example in Radiant
See Also
nn
to generate results
summary.nn
to summarize results
predict.nn
for prediction
Examples
result <- nn(titanic, "survived", c("pclass", "sex"), lev = "Yes")
plot(result, plots = "net")
plot(result, plots = "olden")