# Exits
if (!requireNamespace("RSNNS", quietly = TRUE)) {
exit_file("Package RSNNS missing")
}
if (!requireNamespace("NeuralNetTools", quietly = TRUE)) {
exit_file("Package NeuralNetTools missing")
}
# # Load required packages
# suppressMessages({
# library(RSNNS)
# library(NeuralNetTools)
# })
# Generate Friedman benchmark data
friedman1 <- gen_friedman(seed = 101)
# Fit model(s)
set.seed(101) # for reproducibility
fit <- RSNNS::mlp(
x = subset(friedman1, select = -y),
y = friedman1$y,
size = 10,
linOut = TRUE,
maxit = 1000
)
# Compute VI scores
vis1 <- vi_model(fit)
vis2 <- vi_model(fit, type = "garson")
# Expectations for `vi_model()`
expect_identical(
current = vis1$Importance,
target = NeuralNetTools::olden(fit, bar_plot = FALSE)$importance
)
expect_identical(
current = vis2$Importance,
target = NeuralNetTools::garson(fit, bar_plot = FALSE)$rel_imp
)
# # Expectations for `get_training_data()`
# expect_identical(
# current = vip:::get_training_data.default(fit),
# target = friedman1
# )
#
# # Expectations for `get_feature_names()`
# expect_identical(
# current = vip:::get_feature_names.default(fit),
# target = paste0("x", 1L:10L)
# )
# Call `vip::vip()` directly
p <- vip(fit, method = "model", include_type = TRUE)
# Expect `p` to be a `"gg" "ggplot"` object
expect_identical(
current = class(p),
target = c("gg", "ggplot")
)
# Display VIPs side by side
grid.arrange(
vip(vis1, include_type = TRUE),
vip(vis2, include_type = TRUE),
p,
nrow = 1
)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.