mlr3learners 0.5.0

• Fixed the internal encoding of the positive class for classification learners
  based on glm and glmnet (#199). While predictions in previous versions
  were correct, the estimated coefficients had the wrong sign.
• Reworked handling of lambda and s for glmnet learners (#197).
• Learners based on glmnet now support to extract selected features (#200).
• Learners based on kknn now raise an exception if k >= n (#191).
• Learners based on ranger now come with a virtual hyperparameter mtry.ratio
  to set the hyperparameter mtry based on the proportion of features to use.
• Multiple learners now support the extraction of the log-likelihood (via method
  $loglik(), allowing to calculate measures like AIC or BIC in mlr3 (#182).

mlr3learners 0.4.5

• Fixed SVM learners for new release of package e1071.

mlr3learners 0.4.4

• Changed hyperparameters of all learners to make them run sequentially in their
  defaults.
  The new function set_threads() in mlr3 provides a generic way to set the
  respective hyperparameter to the desired number of parallel threads.
• Added survival:aft objective to surv.xgboost
• Removed hyperparameter predict.all from ranger learners (#172).

mlr3learners 0.4.3

v0.4.3

import predict

mlr3learners 0.4.2

Fixed a bug in the survival random forest LearnerSurvRanger.

mlr3learners 0.4.1

• Disabled some glmnet tests on solaris.
• Removed dependency on orphaned package bibtex.

mlr3learners 0.4.0

• Fixed a potential label switch in classif.glmnet and classif.cv_glmnet
  with predict_type set to "prob" (#155).
• Fixed learners from package glmnet to be more robust if the order of
  features has changed between train and predict.

mlr3learners 0.2.0

• Split {glmnet} learner into cv_glmnet and glmnet (#99)
• {glmnet} learners: Add predict.gamma and newoffset arg (#98)
• We now test that all learners can be constructed without parameters.
• A new custom "Paramtest" which lives inst/paramtest was added.
  This test checks against the arguments of the upstream train & predict functions and ensures that all parameters are implemented in the respective mlr3 learner. (#96)
• A lot missing parameters were added to learners. See #96 for a complete list.
• Add parameter interaction_constraints to {xgboost} learners (#97).
• There is now a vignette "Additional Learners" listing all external learners which live in the mlr3learners organization.
  See mlr3learners.drat for easy installation.

mlr3learners 0.1.5

• Added parameter and parameter dependencies to regr.glmnet, regr.km,
  regr.ranger, regr.svm, regr.xgboost, classif.glmnet, classif.lda,
  classif.naivebayes, classif.qda, classif.ranger and classif.svm.
• glmnet: Added relax parameter (v3.0)
• xgboost: Updated parameters for v0.90.0.2

mlr3learners 0.1.4

• Fixed a bug in *.xgboost and *.svm which was triggered if columns
  were reordered between $train() and $predict().