code: def test_higher_variance_threshold(iris_split_dataset_and_model_rf):
      # Arrange
      _, test_ds, clf = iris_split_dataset_and_model_rf
  
      # Act
      result = UnusedFeatures(feature_variance_threshold=2).run(
          test_ds, clf
      )
  
      # Assert
      assert_that(
          set(result.value["used features"]),
          equal_to(
              {
                  "petal width (cm)",
                  "petal length (cm)",
                  "sepal length (cm)",
              }
          ),
      )
      assert_that(
          set(result.value["unused features"]["high variance"]),
          equal_to(set()),
      )
      assert_that(
          set(result.value["unused features"]["low variance"]),
          equal_to({"sepal width (cm)"}),
      )
  
imports: from hamcrest import assert_that, equal_to, greater_than, has_length
  from deepchecks.tabular.checks.model_evaluation import UnusedFeatures
label_desc: Use image node_id 4 for calling a global function with example usage: test_higher_variance_threshold(iris_split_dataset_and_model_rf) without return types