Version 2.16 • mlr

mlr 2.16.0

CRAN release: 2019-11-26

There is now a reference grouping for all functions on the pkgdown site (https://mlr.mlr-org.com/reference/index.html)
CI testing now only on Circle CI (previously Travis CI)

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)

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

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.

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)
Bugfix: Allow method = "md" of filter randomForestSRC_var.select to set the value returned for features below its threshold to NA (Issue #2687)
Bugfix: With the new praznik v7.0.0 release filter praznik_CMIM does no longer return a result for logical features. See https://gitlab.com/mbq/praznik/issues/19 for more information