mlr3learners
Essential machine learning algorithms wrapped as learners for mlr3
mlr3learners spends its releases absorbing upstream churn
◆Recent moves
- 2mo ago
predict_raw across all learners, plus probit and ranger internals
The broadest release in this window: every learner can retain raw upstream prediction objects, logistic regression gains a link parameter for probit, and ranger learners expose their native model and local importance. Continues the trend of exposing rather than hiding the wrapped models.
View source ↗ - 8mo ago
xgboost 3.1.2.1 compatibility
A compatibility-only release with a single line of change. Representative of how much of this package's cadence is upstream-driven.
View source ↗ - 9mo ago
Uncertainty estimation methods for ranger regression
Adds ensemble standard deviation and law-of-total-variance uncertainty estimates to regr.ranger, and lets ranger's out-of-bag error be stored without keeping the model. Real predictive capability rather than compatibility work.
View source ↗ - 10mo ago
Development snapshot: LDA test adjustment
A development-version tag containing a single test change. Not a user-facing release.
View source ↗ - 1y ago
kknn learners restored after returning to CRAN
Re-adds classif.kknn and regr.kknn, reversing the removal forced one release earlier. Read alongside 0.11.0 this is a restoration, not a new capability.
View source ↗ - 1y ago
kknn learners removed after CRAN archival
A breaking removal forced by kknn's departure from CRAN, alongside mlr3 1.0.0 compatibility. The clearest illustration of how exposed this package is to upstream decisions.
View source ↗