Plot model loss over epochs

Usage

# S3 method for brulee_mlp
autoplot(object, ...)

# S3 method for brulee_logistic_reg
autoplot(object, ...)

# S3 method for brulee_multinomial_reg
autoplot(object, ...)

# S3 method for brulee_linear_reg
autoplot(object, ...)

Arguments

object: A brulee_mlp, brulee_logistic_reg, brulee_multinomial_reg, or brulee_linear_reg object.
...: Not currently used

Value

A ggplot object.

Details

This function plots the loss function across the available epochs. A vertical line shows the epoch with the best loss value.

Examples

# \donttest{
if (torch::torch_is_installed()) {
 library(ggplot2)
 library(recipes)
 theme_set(theme_bw())

 data(ames, package = "modeldata")

 ames$Sale_Price <- log10(ames$Sale_Price)

 set.seed(1)
 in_train <- sample(1:nrow(ames), 2000)
 ames_train <- ames[ in_train,]
 ames_test  <- ames[-in_train,]

 ames_rec <-
  recipe(Sale_Price ~ Longitude + Latitude, data = ames_train) %>%
    step_normalize(all_numeric_predictors())

 set.seed(2)
 fit <- brulee_mlp(ames_rec, data = ames_train, epochs = 50, batch_size = 32)

 autoplot(fit)
}
#> Loading required package: dplyr
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
#> 
#> Attaching package: ‘recipes’
#> The following object is masked from ‘package:stats’:
#> 
#>     step
#> Warning: 'batch_size' is only used for the SGD optimizer.

# }