tune (version 1.0.0)

expo_decay: Exponential decay function

Description

expo_decay() can be used to increase or decrease a function exponentially over iterations. This can be used to dynamically set parameters for acquisition functions as iterations of Bayesian optimization proceed.

Usage

expo_decay(iter, start_val, limit_val, slope = 1/5)

Value

A single numeric value.

Arguments

iter

An integer for the current iteration number.

start_val

The number returned for the first iteration.

limit_val

The number that the process converges to over iterations.

slope

A coefficient for the exponent to control the rate of decay. The sign of the slope controls the direction of decay.

Details

Note that, when used with the acquisition functions in tune(), a wrapper would be required since only the first argument would be evaluated during tuning.

Examples

# \donttest{
library(tibble)
library(purrr)
library(ggplot2)
library(dplyr)
tibble(
  iter = 1:40,
  value = map_dbl(
    1:40,
    expo_decay,
    start_val = .1,
    limit_val = 0,
    slope = 1 / 5
  )
) %>%
  ggplot(aes(x = iter, y = value)) +
  geom_path()
# }