NEWS.md

In stablelearner: Stability Assessment of Statistical Learning Methods

stablelearner 0.1-9

• Fix "donttest" examples, broken by partykit 1.3-0.

• Import functions selectively, as needed, from graphics and partykit rather than the entire namespaces.

stablelearner 0.1-8

• Code repository changed from R-Forge to Codeberg at: https://codeberg.org/zeileis/stablelearner/

• Added basic altdoc page with overview and documentation at: https://zeileis.codeberg.page/stablelearner/

stablelearner 0.1-7

• Fix small bug in splithalf() sampling for stability(). In case of an uneven number of observations in the learning sample some small overlap in the two splitted halves would occur. This is avoided now by dropping one random observation now and restricting both halves to be always of the same size. Reported by Constantin Wiegand along with two further small improvements: Warnings about lack of variance in predictions on learning samples and avoiding manual triggering of the garbage collector.

stablelearner 0.1-6

• Improve non-anchored links in manual pages (prompted by CRAN).

stablelearner 0.1-5

• The as.stabletree() method for RandomForest objects (party package) is now registered as an S3 (rather than S4) method.

• Environment .stabEnv is only used internally by stabletree() and hence not exported anymore in NAMESPACE.

stablelearner 0.1-4

• Z takes over maintenance from MP.

• Fix checks for sampler specifications where a logical of length 2 is now correctly aggregated with all().

stablelearner 0.1-3

• Small improvements for CRAN checks.

stablelearner 0.1-2

• Changed default sampling method in stabletree() from bootstrap() to subsampling() with default fraction of v = 0.632.

• as.stabletree() coercion generic added which allows to coerce a randomForest (randomForest package), RandomForest (party package), cforest (partykit package) or ranger (ranger package) to a stabletree object.

• Added a vignette on the variable and cutpoint selection analysis of random forests.

stablelearner 0.1-1

• Project stablelearner has been launched and a stable version of the package has been uploaded to CRAN.

• stability() is available to estimate the stability of the results from a given supervised statistical learning method.

• stabletree() is available to estimate the stability of the results from recursive partitioning.

stablelearner documentation built on Aug. 28, 2026, 9:06 a.m.