Splits data into bootstrap samples (sampling with replacement). Hyperparameters are the number of bootstrap iterations (repeats, default: 30) and the ratio of observations to draw per iteration (ratio, default: 1) for the training set.

Format

R6::R6Class inheriting from Resampling.

Construction

ResamplingBootstrap$new()
mlr_resamplings$get("bootstrap")
rsmp("bootstrap")

Fields

See Resampling.

Methods

See Resampling.

Parameters

  • repeats :: integer(1)
    Number of repetitions.

  • ratio :: numeric(1)
    Ratio of observations to put into the training set.

See also

Dictionary of Resamplings: mlr_resamplings

as.data.table(mlr_resamplings) for a complete table of all (also dynamically created) Resampling implementations.

Examples

# Create a task with 10 observations task = tsk("iris") task$filter(1:10) # Instantiate Resampling rb = rsmp("bootstrap", repeats = 2, ratio = 1) rb$instantiate(task) # Individual sets: rb$train_set(1)
#> [1] 1 1 2 2 4 6 7 7 8 8
rb$test_set(1)
#> [1] 3 5 9 10
intersect(rb$train_set(1), rb$test_set(1))
#> integer(0)
# Internal storage: rb$instance$M # Matrix of counts
#> #> [,1] [,2] #> [1,] 2 0 #> [2,] 2 0 #> [3,] 0 1 #> [4,] 1 0 #> [5,] 0 1 #> [6,] 1 2 #> [7,] 2 1 #> [8,] 2 4 #> [9,] 0 0 #> [10,] 0 1