mlr3 (version 0.1.4)

ResamplingBootstrap: Bootstrap Resampling

Description

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

# NOT RUN {
# 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$train_set(1)
rb$test_set(1)
intersect(rb$train_set(1), rb$test_set(1))

# Internal storage:
rb$instance$M # Matrix of counts
# }

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