# makeResampleInstance

From mlr v2.10
0th

Percentile

##### Instantiates a resampling strategy object.

This class encapsulates training and test sets generated from the data set for a number of iterations. It mainly stores a set of integer vectors indicating the training and test examples for each iteration.

##### Usage
makeResampleInstance(desc, task, size, ...)
##### Arguments
desc
[ResampleDesc | character(1)] Resampling description object or name of resampling strategy. In the latter case makeResampleDesc will be called internally on the string.
[Task] Data of task to resample from. Prefer to pass this instead of size.
size
[integer] Size of the data set to resample. Can be used instead of task.
...
[any] Passed down to makeResampleDesc in case you passed a string in desc. Otherwise ignored.
##### Details

Object slots:

desc [ResampleDesc]
See argument.
size [integer(1)]
See argument.
train.inds [list of integer]
List of of training indices for all iterations.
test.inds [list of integer]
List of of test indices for all iterations.
group [factor]
Optional grouping of resampling iterations. This encodes whether specfic iterations 'belong together' (e.g. repeated CV), and it can later be used to aggregate performance values accordingly. Default is 'factor()'.

##### Value

[ResampleInstance].

Other resample: ResamplePrediction, ResampleResult, addRRMeasure, getRRPredictionList, getRRPredictions, getRRTaskDescription, makeResampleDesc, resample

##### Aliases
• makeResampleInstance
• ResampleInstance
##### Examples
rdesc = makeResampleDesc("Bootstrap", iters = 10)