Prepare release (#150)

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: mlr3filters
 Title: Filter Based Feature Selection for 'mlr3'
-Version: 0.7.0-9000
+Version: 0.7.1
 Authors@R: c(
     person("Patrick", "Schratz", , "[email protected]", role = "aut",
            comment = c(ORCID = "0000-0003-0748-6624")),

NEWS.md

@@ -1,3 +1,9 @@
+# mlr3filters 0.7.1
+
+- Tagged multiple filters to be able of gracefully handling missing values.
+- Added more supported feature types to FilterCarScore.
+- Improved documentation.
+
 # mlr3filters 0.7.0
 
 - Features are now checked for missing values to improve error messages (#140)

R/FilterCarScore.R

@@ -55,7 +55,7 @@ FilterCarScore = R6Class("FilterCarScore",
         id = "carscore",
         task_types = "regr",
         param_set = param_set,
-        feature_types = "numeric",
+        feature_types = c("logical", "integer", "numeric"),
         packages = "care",
         label = "Correlation-Adjusted coRrelation Score",
         man = "mlr3filters::mlr_filters_carscore"
@@ -66,7 +66,7 @@ FilterCarScore = R6Class("FilterCarScore",
   private = list(
     .calculate = function(task, nfeat) {
       target = task$truth()
-      features = task$data(cols = task$feature_names)
+      features = as_numeric_matrix(task$data(cols = task$feature_names))
 
       pv = self$param_set$values
       scores = invoke(care::carscore,

R/helper.R

@@ -13,6 +13,13 @@ catn = function(..., file = "") {
   cat(paste0(..., collapse = "\n"), "\n", sep = "", file = file)
 }
 
+as_numeric_matrix = function(x) {
+  x = as.matrix(x)
+  if (is.logical(x)) {
+    storage.mode(x) = "double"
+  }
+  x
+}
 
 test_matching_task_type = function(task_type, object, class) {
   fget = function(tab, i, j, key) {