Predict individual distribution parameters

Usage

# S3 method for reservr_keras_model
predict(object, data, as_matrix = FALSE, ...)

Arguments

object: A compiled and trained reservr_keras_model.
data: Input data compatible with the model.
as_matrix: Return a parameter matrix instead of a list structure?
...: ignored

Value

A parameter list suitable for the with_params argument of the distribution family used for the model. Contains one set of parameters per row in data.

Examples

if (interactive() && keras::is_keras_available()) {
  dist <- dist_exponential()
  params <- list(rate = 1.0)
  N <- 100L
  rand_input <- runif(N)
  x <- dist$sample(N, with_params = params)

  tf_in <- keras::layer_input(1L)
  mod <- tf_compile_model(
    inputs = list(tf_in),
    intermediate_output = tf_in,
    dist = dist,
    optimizer = keras::optimizer_adam(),
    censoring = FALSE,
    truncation = FALSE
  )

  tf_fit <- fit(
    object = mod,
    x = k_matrix(rand_input),
    y = x,
    epochs = 10L,
    callbacks = list(
      callback_debug_dist_gradients(mod, k_matrix(rand_input), x)
    )
  )

  tf_preds <- predict(mod, data = k_matrix(rand_input))
}