bootstrap: Bootstrap resampling

View source: R/bootstrap_class.R

bootstrapR Documentation

Bootstrap resampling

Description

In bootstrap resampling a subset of samples is selected at random with replacement to form a training set. Any sample not selected for training is included in the test set. This process is repeated many times, and performance metrics are computed for each repetition.

Usage

bootstrap(number_of_repetitions = 100, collect, ...)

Arguments

number_of_repetitions

(numeric, integer) The number of bootstrap repetitions. The default is 100.

collect

(character) The name of a model output to collect over all bootstrap repetitions, in addition to the input metric.

...

Additional slots and values passed to struct_class.

Value

A bootstrap object with the following output slots:

results (data.frame)
metric (data.frame)
collected (logical, list)

Inheritance

A bootstrap object inherits the following struct classes:

⁠[bootstrap]⁠ >> ⁠[resampler]⁠ >> ⁠[iterator]⁠ >> ⁠[struct_class]⁠

Examples

M = bootstrap(
      number_of_repetitions = 10,
      collect = "vip")

I = bootstrap(number_of_repetitions = 10, collect = 'vip')

computational-metabolomics/structToolbox documentation built on July 5, 2024, 12:18 p.m.