View source: R/resample_class.R
resample | R Documentation |
New training sets are generated from the original data by selecting samples at random. This can be based on levels in a factor or on the whole dataset.
resample(
number_of_iterations = 10,
method = "split_data",
factor_name,
p_train = 0.8,
collect = NULL,
...
)
number_of_iterations |
(numeric, integer) The number of training sets to generate. The default is |
method |
(character) Resampling method. Allowed values are limited to the following:
The default is |
factor_name |
(character) The name of a sample-meta column to use. |
p_train |
(numeric) The proportion of samples selected for the training set. The default is |
collect |
(NULL, character) The name of a model output to collect over all bootstrap repetitions, in addition to the input metric. The default is |
... |
Additional slots and values passed to |
A resample
object with the following output
slots:
results.training | (data.frame) |
results.testing | (data.frame) |
metric | (data.frame) |
collected | (list) |
metric.train | (numeric) |
metric.test | (numeric) |
A resample
object inherits the following struct
classes:
[resample]
>> [resampler]
>> [iterator]
>> [struct_class]
M = resample(
number_of_iterations = 100,
method = "split_data",
factor_name = "V1",
p_train = 0.75,
collect = NULL)
I = resample(
number_of_iterations = 10,
factor_name = 'Species',
method = 'split_data',
p_train = 0.8)
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