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NEWS.md

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sl3 1.4.2

  • Updates to variable importance functionality, including calculation of risk ratio and risk differences under covariate deletion or permutation.
  • Addition of a importance_plot to summarize variable importance findings.
  • Additions of new methods reparameterize and retrain to Lrnr_base, which allows modification of the covariate set while training on a conserved task and prediction on a new task using previously trained learners, respectively.

sl3 1.4.1

  • [TODO]

sl3 1.4.0

  • [TODO]

sl3 1.3.9

  • [TODO]

sl3 1.3.8

  • Updates to variable importance functionality, including use of risk ratios.
  • Change Lrnr_hal9001 and Lrnr_glmnet to respect observation-level IDs.
  • Removal of Remotes and deprecation of Lrnr_rfcde and Lrnr_condensier:
    • Both of these learner classes provided support for conditional density estimation (CDE) and were useful when support for CDE was more limited. Unfortunately, both packages are un-maintained or updated only very sporadically, resulting in both frequent bugs and presenting an obstacle for an eventual CRAN release (both packages are GitHub-only).
    • Lrnr_rfcde wrapped https://github.com/tpospisi/RFCDE, a sporadically maintained tool for conditional density estimation (CDE). Support for this has been removed in favor of built-in CDE tools, including, among others, Lrnr_density_semiparametric.
    • Lrnr_condensier wrapped https://github.com/osofr/condensier, which provided a pooled hazards approach to CDE. This package contained an implementation error (osofr/condensier#15) and was removed from CRAN. Support for this has been removed in favor of Lrnr_density_semiparametric and Lrnr_haldensify, both of which more reliably provide CDE support.

sl3 1.3.7

  • Sampling methods for Monte Carlo integration and related procedures.
  • A metalearner for the cross-validation selector (discrete super learner).
  • A learner for bounding, including support for bounded losses.
  • Resolution of a number of older issues (see #264).
  • Relaxation of checks inside Stack objects for time series learners.
  • Addition of a learner property table to README.Rmd.
  • Maintenance and documentation updates.

sl3 1.3.5

  • Overhaul of data preprocessing.
  • New screening methods and convex combination in Lrnr_nnls.
  • Bug fixes, including covariate subsetting and better handling of NAs.
  • Package and documentation cleanup; continuous integration and testing fixes.
  • Reproducibility updates (including new versioning and DOI minting).

sl3 1.3.0

  • Fixes incorrect handling of missingness in the automatic imputation procedure.
  • Adds new standard learners, including from the gam and caret packages.
  • Adds custom learners for conditional density estimation, including semiparametric methods based on conditional mean and conditional mean/variance estimation as well as generalized functionality for density estimation via a pooled hazards approach.

sl3 1.2.0

  • Default metalearners based on task outcome types.
  • Handling of imputation internally in task objects.
  • Addition of several new learners, including from the gbm, earth, polspline packages.
  • Fixing errors in existing learners (e.g., subtle parallelization in xgboost and ranger).
  • Support for multivariate outcomes
  • Sets default cross-validation to be revere-style.
  • Support for cross-validated super learner and variable importance.

sl3 1.1.0

  • A full-featured and stable release of the project.
  • Numerous learners are included and many bugs have been fixed relative to earlier versions (esp v1.0.0) of the software.

sl3 1.0.0

  • An initial stable release.