add missing package to suggests

DESCRIPTION

@@ -47,6 +47,7 @@ Imports:
     ggplot2
 Suggests:
     testthat (>= 3.1.0),
+    CVXR,
     patchwork,
     rpart,
     ranger,

R/learner_fairml_classif_fairzlrm.R

@@ -1,10 +1,10 @@
 #' @title Classification Fair Logistic Regression With Covariance Constraints Learner
 #' @author pfistfl
-#' @details 
+#' @details
 #' Generalized fair regression model from Zafar et al., 2019 implemented via package `fairml`.
 #' The 'unfairness' parameter is set to 0.05 as a default.
 #' The optimized fairness metric is statistical parity.
-#' 
+#'
 #' @name mlr_learners_classif.fairzlrm
 #'
 #' @template class_learner
@@ -13,7 +13,7 @@
 #'
 #' @references
 #' `r format_bib("zafar19a")`
-#' 
+#'
 #' @template seealso_learner
 #' @template example
 #' @export
@@ -31,7 +31,7 @@ LearnerClassifFairzlrm = R6Class("LearnerClassifFairzlrm",
       ps$values = list(unfairness = 0.05, intersect = FALSE)
       super$initialize(
         id = "classif.fairzlrm",
-        packages = "fairml",
+        packages = c("fairml", "CVXR"),
         feature_types = c("integer", "numeric", "factor", "ordered"),
         predict_types = c("response", "prob"),
         properties = "twoclass",

R/learner_fairml_regr_fairzlm.R

@@ -1,10 +1,10 @@
 #' @title Regression Fair Regression With Covariance Constraints Learner
 #' @author pfistfl
-#' @details 
+#' @details
 #' Fair regression model from Zafar et al., 2019 implemented via package `fairml`.
 #' The 'unfairness' parameter is set to 0.05 as a default.
 #' The optimized fairness metric is statistical parity.
-#' 
+#'
 #' @name mlr_learners_regr.fairzlm
 #'
 #' @template class_learner
@@ -31,7 +31,7 @@ LearnerRegrFairzlm = R6Class("LearnerRegrFairzlm",
       ps$values = list(unfairness = 0.05, intersect = FALSE)
       super$initialize(
         id = "regr.fairzlm",
-        packages = "fairml",
+        packages = c("fairml", "CVXR"),
         feature_types = c("integer", "numeric", "factor", "ordered"),
         predict_types = c("response"),
         param_set = ps,

tests/testthat/test_learners_fairml.R

@@ -24,9 +24,10 @@ test_that("regr.fairfrrm", {
 test_that("regr.fairzlm", {
     skip_on_cran()
     skip_if_not_installed("fairml")
+    skip_if_not_installed("CVXR")
     learner = lrn("regr.fairzlm", unfairness = 0.5)
     out = expect_learner(learner)
-    
+
     task = TaskRegr$new("long", fairml::national.longitudinal.survey, target = "income06")
     task$col_roles$pta = "gender"
     simple_autotest(learner, task)
@@ -38,6 +39,7 @@ test_that("regr.fairzlm", {
 test_that("classif.fairzlrm", {
     skip_on_cran()
     skip_if_not_installed("fairml")
+    skip_if_not_installed("CVXR")
     learner = lrn("classif.fairzlrm", unfairness = 0.2)
     out = expect_learner(learner)