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mlr3resampling
View on CRAN: Click
here
Download and install mlr3resampling package within the R console
Install from CRAN:
install.packages("mlr3resampling")
Install from Github:
library("remotes")
install_github("cran/mlr3resampling")
Install by package version:
library("remotes")
install_version("mlr3resampling", "2024.4.14")
Attach the package and use:
library("mlr3resampling")
Maintained by
Toby Hocking
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-12-21
Latest Update: 2024-02-29
Description:
A supervised learning algorithm inputs a train set,
and outputs a prediction function, which can be used on a test set.
If each data point belongs to a group
(such as geographic region, year, etc), then
how do we know if it is possible to train on one group, and predict
accurately on another group? Cross-validation can be used to determine
the extent to which this is possible, by first assigning fold IDs from
1 to K to all data (possibly using stratification, usually by group
and label). Then we loop over test sets (group/fold combinations),
train sets (same group, other groups, all groups), and compute
test/prediction accuracy for each combination. Comparing
test/prediction accuracy between same and other, we can determine the
extent to which it is possible (perfect if same/other have similar
test accuracy for each group; other is usually somewhat less accurate
than same; other can be just as bad as featureless baseline when the
groups have different patterns).
For more information,
describes the method in depth.
How many train samples are required to get accurate predictions on a
test set? Cross-validation can be used to answer this question, with
variable size train sets.
How to cite:
Toby Hocking (2023). mlr3resampling: Resampling Algorithms for 'mlr3' Framework. R package version 2024.4.14, https://cran.r-project.org/web/packages/mlr3resampling
Previous versions and publish date:
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Other R packages that mlr3resampling depends,
imports, suggests or enhances
Functions, R codes and Examples using
the mlr3resampling R package
Some associated functions: ResamplingSameOtherCV . ResamplingVariableSizeTrainCV . score .
Some associated R codes: ResamplingBase.R . ResamplingSameOtherCV.R . ResamplingVariableSizeTrainCV.R . score.R . Full mlr3resampling package functions and examples
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