BREAKING CHANGE: remove $loglik method from all learners (#1207)

NEWS.md

@@ -2,6 +2,7 @@
 
 * fix: Quantiles must not ascend with probabilities.
 * refactor: Replace `tsk("boston_housing")` with `tsk("california_housing")`.
+* BREAKING CHANGE: Remove ``$loglik()`` method from all learners.
 
 # mlr3 0.21.1
 

R/Learner.R

@@ -59,9 +59,6 @@
 #' * `oob_error(...)`: Returns the out-of-bag error of the model as `numeric(1)`.
 #'   The learner must be tagged with property `"oob_error"`.
 #'
-#' * `loglik(...)`: Extracts the log-likelihood (c.f. [stats::logLik()]).
-#'   This can be used in measures like [mlr_measures_aic] or [mlr_measures_bic].
-#'
 #' * `internal_valid_scores`: Returns the internal validation score(s) of the model as a named `list()`.
 #'   Only available for [`Learner`]s with the `"validation"` property.
 #'   If the learner is not trained yet, this returns `NULL`.

R/MeasureAIC.R

@@ -40,12 +40,14 @@ MeasureAIC = R6Class("MeasureAIC",
   private = list(
     .score = function(prediction, learner, ...) {
       learner = learner$base_learner()
-      if ("loglik" %nin% learner$properties) {
-        return(NA_real_)
-      }
-
       k = self$param_set$values$k %??% 2
-      return(stats::AIC(learner$loglik(), k = k))
+
+      tryCatch({
+        return(stats::AIC(stats::logLik(learner$model), k = k))
+      }, error = function(e) {
+        warningf("Learner '%s' does not support AIC calculation", learner$id)
+        return(NA_real_)
+      })
     }
   )
 )

R/MeasureBIC.R

@@ -38,11 +38,13 @@ MeasureBIC = R6Class("MeasureBIC",
   private = list(
     .score = function(prediction, learner, ...) {
       learner = learner$base_learner()
-      if ("loglik" %nin% learner$properties) {
-        return(NA_real_)
-      }
 
-      return(stats::BIC(learner$loglik()))
+      tryCatch({
+        return(stats::BIC(stats::logLik(learner$model)))
+      }, error = function(e) {
+        warningf("Learner '%s' does not support BIC calculation", learner$id)
+        return(NA_real_)
+      })
     }
   )
 )

R/mlr_reflections.R

@@ -118,7 +118,7 @@ local({
   )
 
   ### Learner
-  tmp = c("featureless", "missings", "weights", "importance", "selected_features", "oob_error", "loglik", "hotstart_forward", "hotstart_backward", "validation", "internal_tuning", "marshal")
+  tmp = c("featureless", "missings", "weights", "importance", "selected_features", "oob_error", "hotstart_forward", "hotstart_backward", "validation", "internal_tuning", "marshal")
   mlr_reflections$learner_properties = list(
     classif = c(tmp, "twoclass", "multiclass"),
     regr = tmp