scikit-learn
diff --git a/‎sklearn/random_projection.py
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+1-1Lines changed: 1 addition & 1 deletion b/‎sklearn/random_projection.py
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+1-1Lines changed: 1 addition & 1 deletion
diff --git a/‎sklearn/tests/test_random_projection.py
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+8Lines changed: 8 additions & 0 deletions b/‎sklearn/tests/test_random_projection.py
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+8Lines changed: 8 additions & 0 deletions
@@ -129,7 +129,7 @@ def johnson_lindenstrauss_min_dim(n_samples, *, eps=0.1):
             % n_samples)
 
     denominator = (eps ** 2 / 2) - (eps ** 3 / 3)
-    return (4 * np.log(n_samples) / denominator).astype(int)
+    return (4 * np.log(n_samples) / denominator).astype(np.int64)
 
 
 def _check_density(density, n_features):
 
@@ -352,3 +352,11 @@ def test_works_with_sparse_data():
                                      random_state=1).fit(sp.csr_matrix(data))
         assert_array_almost_equal(densify(rp_dense.components_),
                                   densify(rp_sparse.components_))
+
+
+def test_johnson_lindenstrauss_min_dim():
+    """Test Johnson-Lindenstrauss for small eps.
+
+    Regression test for #17111: before #19374, 32-bit systems would fail.
+    """
+    assert johnson_lindenstrauss_min_dim(100, eps=1e-5) == 368416070986