Interpretation metrics from a TabNet model
Interpretation metrics from a TabNet model
tabnet_explain(object, new_data)
object |
a TabNet fit object |
new_data |
a data.frame to obtain interpretation metrics. |
Returns a list with
M_explain: the aggregated feature importance masks as detailed in
TabNet's paper.
masks a list containing the masks for each step.
if (torch::torch_is_installed()) {
set.seed(2021)
n <- 1000
x <- data.frame(
x = runif(n),
y = runif(n),
z = runif(n)
)
y <- x$x
fit <- tabnet_fit(x, y, epochs = 20,
num_steps = 1,
batch_size = 512,
attention_width = 1,
num_shared = 1,
num_independent = 1)
ex <- tabnet_explain(fit, x)
}Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.