scikit-learn · NelleV · Aug 14, 2017 · Aug 4, 2017 · Aug 9, 2017 · Aug 9, 2017
diff --git a/doc/whats_new.rst b/doc/whats_new.rst
@@ -11,6 +11,18 @@ Version 0.20 (under development)
 Changed models
 --------------
 
+The following estimators and functions, when fit with the same data and
+parameters, may produce different models from the previous version. This often
+occurs due to changes in the modelling logic (bug fixes or enhancements), or in
+random sampling procedures.
+
+- :class:`decomposition.IncrementalPCA` in Python 2 (bug fix)
+
+Details are listed in the changelog below.
+
+(While we are trying to better inform users by providing this information, we
+cannot assure that this list is complete.)
+
 Changelog
 ---------
 
@@ -24,6 +36,16 @@ Classifiers and regressors
   via ``n_iter_no_change``, ``validation_fraction`` and ``tol``. :issue:`7071`
   by `Raghav RV`_
 
+Bug fixes
+.........
+
+Decomposition, manifold learning and clustering
+
+- Fixed a bug where the ``partial_fit`` method of
+  :class:`decomposition.IncrementalPCA` used integer division instead of float
+  division on Python 2 versions. :issue:`9492` by
+  :user:`James Bourbeau <jrbourbeau>`.
+
 
 Version 0.19
 ============
@@ -160,7 +182,7 @@ Model selection and evaluation
   :issue:`8120` by `Neeraj Gangwar`_.
 
 - Added a scorer based on :class:`metrics.explained_variance_score`.
-  :issue:`9259` by `Hanmin Qin <https://github.com/qinhanmin2014>`_. 
+  :issue:`9259` by `Hanmin Qin <https://github.com/qinhanmin2014>`_.
 
 Miscellaneous
 

diff --git a/sklearn/decomposition/incremental_pca.py b/sklearn/decomposition/incremental_pca.py
@@ -4,6 +4,7 @@
 #         Giorgio Patrini
 # License: BSD 3 clause
 
+from __future__ import division
 import numpy as np
 from scipy import linalg
 

diff --git a/sklearn/decomposition/tests/test_incremental_pca.py b/sklearn/decomposition/tests/test_incremental_pca.py
@@ -273,3 +273,27 @@ def test_whitening():
         assert_almost_equal(X, Xinv_ipca, decimal=prec)
         assert_almost_equal(X, Xinv_pca, decimal=prec)
         assert_almost_equal(Xinv_pca, Xinv_ipca, decimal=prec)
+
+
+def test_incremental_pca_partial_fit_float_division():
+    # Test to ensure float division is used in all versions of Python
+    # (non-regression test for issue #9489)
+
+    rng = np.random.RandomState(0)
+    A = rng.randn(5, 3) + 2
+    B = rng.randn(7, 3) + 5
+
+    pca = IncrementalPCA(n_components=2)
+    pca.partial_fit(A)
+    # Set n_samples_seen_ to be a floating point number instead of an int
+    pca.n_samples_seen_ = float(pca.n_samples_seen_)
+    pca.partial_fit(B)
+    singular_vals_float_samples_seen = pca.singular_values_
+
+    pca2 = IncrementalPCA(n_components=2)
+    pca2.partial_fit(A)
+    pca2.partial_fit(B)
+    singular_vals_int_samples_seen = pca2.singular_values_
+
+    np.testing.assert_allclose(singular_vals_float_samples_seen,
+                               singular_vals_int_samples_seen)