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mlr 2.16.0
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@pat-s pat-s released this 26 Nov 22:22
· 355 commits to master since this release
v2.16.0
ce82484

package infrastructure

learners - general

  • fixed a bug in classif.xgboost which prevented passing a watchlist for binary tasks. This was caused by a suboptimal internal label inversion approach. Thanks to @001ben for reporting (#32) (@mllg)
  • update fda.usc learners to work with package version >=2.0
  • update glmnet learners to upstream package version 3.0.0
  • update xgboost learners to upstream version 0.90.2 (@pat-s & @be-marc, #2681)
  • Updated ParamSet for learners classif.gbm and regr.gbm. Specifically, param shrinkage now defaults to 0.1 instead of 0.001. Also more choices for param distribution have been added. Internal parallelization by the package is now suppressed (param n.cores). (@pat-s, #2651)
  • Update parameters for h2o.deeplearning learners (@albersonmiranda, #2668)

misc

  • Add configureMlr() to .onLoad(), possibly fixing some edge cases (#2585) (@pat-s, #2637)

learners - bugfixes

  • h2o.gbm learners were not running until wcol was passed somehow due to an internal bug. In addition, this bug caused another issue during prediction where the prediction data.frame was somehow formatted as a character rather a numeric. Thanks to @nagdevAmruthnath for bringing this up in #2630.

filters - general

  • Bugfix: Allow method = "vh" for filter randomForestSRC_var.select and return informative error message for not supported values. Also argument conservative can now be passed. See #2646 and #2639 for more information (@pat-s, #2649)
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