diff --git a/tests/test_check_estimators.py b/tests/test_check_estimators.py
index 387ba204c..5d4643ff9 100644
--- a/tests/test_check_estimators.py
+++ b/tests/test_check_estimators.py
@@ -6,10 +6,7 @@
 from skmatter.feature_selection import PCovCUR as fPCovCUR
 from skmatter.feature_selection import PCovFPS as fPCovFPS
 from skmatter.linear_model import RidgeRegression2FoldCV  # OrthogonalRegression,
-from skmatter.preprocessing import (
-    KernelNormalizer,
-    StandardFlexibleScaler,
-)
+from skmatter.preprocessing import KernelNormalizer, StandardFlexibleScaler
 
 
 @parametrize_with_checks(
diff --git a/tests/test_sample_simple_cur.py b/tests/test_sample_simple_cur.py
index 6898f3d22..dda1d71aa 100644
--- a/tests/test_sample_simple_cur.py
+++ b/tests/test_sample_simple_cur.py
@@ -1,7 +1,6 @@
 import unittest
 
 import numpy as np
-from sklearn import exceptions
 from sklearn.datasets import fetch_california_housing as load
 
 from skmatter.sample_selection import CUR, FPS
@@ -10,12 +9,12 @@
 class TestCUR(unittest.TestCase):
     def setUp(self):
         self.X, _ = load(return_X_y=True)
-        self.X = FPS(n_to_select=100).fit(self.X).transform(self.X)
+        self.X = self.X[FPS(n_to_select=100).fit(self.X).selected_idx_]
         self.n_select = min(20, min(self.X.shape) // 2)
 
     def test_bad_transform(self):
         selector = CUR(n_to_select=2)
-        with self.assertRaises(exceptions.NotFittedError):
+        with self.assertRaises(ValueError):
             _ = selector.transform(self.X)
 
     def test_restart(self):