diff --git a/mapclassify/tests/test_classify.py b/mapclassify/tests/test_classify.py
index a1b70eff..c8359d5d 100644
--- a/mapclassify/tests/test_classify.py
+++ b/mapclassify/tests/test_classify.py
@@ -7,9 +7,9 @@
 
 def _assertions(a, b):
     assert a.k == b.k
-    assert a.yb.all() == b.yb.all()
-    assert a.bins.all() == b.bins.all()
-    assert a.counts.all() == b.counts.all()
+    assert (a.yb == b.yb).all()
+    assert (a.bins == b.bins).all()
+    assert (a.counts == b.counts).all()
 
 
 class TestClassify:
@@ -33,6 +33,12 @@ def test_fisher_jenks(self):
         b = mapclassify.FisherJenks(self.x, k=3)
         _assertions(a, b)
 
+    # mapclassify\classifiers.py:FisherJenksSampled.__init__
+    # 2028  ids = np.random.randint(0, n, int(n * pct))
+    @pytest.mark.xfail(
+        reason="Stochastic. Passing a.s. requires random samples "
+        "to be the same in both instances. "
+    )
     def test_fisher_jenks_sampled(self):
         a = mapclassify.classify(
             self.x, "FisherJenksSampled", k=3, pct_sampled=0.5, truncate=False
@@ -69,16 +75,34 @@ def test_jenks_caspall_forced(self):
         b = mapclassify.JenksCaspallForced(self.x, k=3)
         _assertions(a, b)
 
+    # mapclassify\classifiers.py:JenksCaspallSampled.__init__
+    # 2224  ids = np.random.randint(0, n, int(n * pct))
+    @pytest.mark.xfail(
+        reason="Stochastic. Passing a.s. requires random samples "
+        "to be the same in both instances. "
+    )
     def test_jenks_caspall_sampled(self):
         a = mapclassify.classify(self.x, "JenksCaspallSampled", pct_sampled=0.5)
         b = mapclassify.JenksCaspallSampled(self.x, pct=0.5)
         _assertions(a, b)
 
+    # KMeans iterates starting from a randomly generated centroids
+    @pytest.mark.xfail(
+        reason="Stochastic. Passing a.s. requires random centroids "
+        "to be the same in both instances. "
+    )
     def test_natural_breaks(self):
         a = mapclassify.classify(self.x, "natural_breaks")
         b = mapclassify.NaturalBreaks(self.x)
         _assertions(a, b)
 
+    # mapclassify\classifiers.py:MaxP._set_bins
+    # 2656  rseeds = np.random.permutation(list(range(k))).tolist()
+    # 2701  rseeds = np.random.permutation(list(range(k))).tolist()
+    @pytest.mark.xfail(
+        reason="Stochastic. Passing a.s. requires random selections "
+        "to be the same in both instances. "
+    )
     def test_max_p_classifier(self):
         a = mapclassify.classify(self.x, "max_p", k=3, initial=50)
         b = mapclassify.MaxP(self.x, k=3, initial=50)