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')