mlr3resampling
Resampling Algorithms for 'mlr3' Framework
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, https://tdhock.github.io/blog/2023/R-gen-new-subsets/ 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.
- Version2024.9.6
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- Last release09/11/2024
Documentation
Team
Toby Hocking
MaintainerShow author detailsBernd Bischl
Michel Lang
Giuseppe Casalicchio
Jakob Richter
Raphael Sonabend
Marc Becker
Patrick Schratz
Sebastian Fischer
Martin Binder
Show author detailsRolesContributorFlorian Pfisterer
Lennart Schneider
Quay Au
Stefan Coors
Insights
Last 30 days
This package has been downloaded 269 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.
Last 365 days
This package has been downloaded 3,774 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jan 24, 2024 with 84 downloads.
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Dependencies
- Imports5 packages
- Suggests11 packages