Merge remote-tracking branch 'upstream/pr/6182'

Author: MechCoder

doc/whats_new.rst

@@ -102,6 +102,9 @@ Enhancements
 Bug fixes
 .........
 
+ - :class:`StratifiedKFold` now raises error if all n_labels for individual classes is less than n_folds.
+ (`#6182 <https://github.com/scikit-learn/scikit-learn/pull/6182>`_) by `Devashish Deshpande`_.
+
  - :class:`RandomizedPCA` default number of `iterated_power` is 2 instead of 3.
  This is a speed up with a minor precision decrease. (`#5141 <https://github.com/scikit-learn/scikit-learn/pull/5141>`_) by `Giorgio Patrini`_.
 

sklearn/cross_validation.py

@@ -519,6 +519,10 @@ def __init__(self, y, n_folds=3, shuffle=False,
  unique_labels, y_inversed = np.unique(y, return_inverse=True)
  label_counts = bincount(y_inversed)
  min_labels = np.min(label_counts)
+ if np.all(self.n_folds > label_counts):
+ raise ValueError("All the n_labels for individual classes"
+ " are less than %d folds."
+ % (self.n_folds))
  if self.n_folds > min_labels:
  warnings.warn(("The least populated class in y has only %d"
  " members, which is too few. The minimum"

sklearn/model_selection/_split.py

@@ -564,6 +564,10 @@ def _make_test_folds(self, X, y=None, labels=None):
  unique_y, y_inversed = np.unique(y, return_inverse=True)
  y_counts = bincount(y_inversed)
  min_labels = np.min(y_counts)
+ if np.all(self.n_folds > y_counts):
+ raise ValueError("All the n_labels for individual classes"
+ " are less than %d folds."
+ % (self.n_folds))
  if self.n_folds > min_labels:
  warnings.warn(("The least populated class in y has only %d"
  " members, which is too few. The minimum"

sklearn/model_selection/tests/test_split.py

@@ -21,6 +21,7 @@
 from sklearn.utils.testing import assert_array_almost_equal
 from sklearn.utils.testing import assert_array_equal
 from sklearn.utils.testing import assert_warns_message
+from sklearn.utils.testing import assert_raise_message
 from sklearn.utils.testing import ignore_warnings
 from sklearn.utils.validation import _num_samples
 from sklearn.utils.mocking import MockDataFrame
@@ -206,7 +207,7 @@ def test_kfold_valueerrors():
 
  # Check that a warning is raised if the least populated class has too few
  # members.
- y = np.array([3, 3, -1, -1, 2])
+ y = np.array([3, 3, -1, -1, 3])
 
  skf_3 = StratifiedKFold(3)
  assert_warns_message(Warning, "The least populated class",
@@ -219,11 +220,21 @@ def test_kfold_valueerrors():
  warnings.simplefilter("ignore")
  check_cv_coverage(skf_3, X2, y, labels=None, expected_n_iter=3)
 
+ # Check that errors are raised if all n_labels for individual
+ # classes are less than n_folds.
+ y = np.array([3, 3, -1, -1, 2])
+
+ assert_raises(ValueError, next, skf_3.split(X2, y))
+
  # Error when number of folds is <= 1
  assert_raises(ValueError, KFold, 0)
  assert_raises(ValueError, KFold, 1)
- assert_raises(ValueError, StratifiedKFold, 0)
- assert_raises(ValueError, StratifiedKFold, 1)
+ error_string = ("k-fold cross-validation requires at least one"
+ " train/test split")
+ assert_raise_message(ValueError, error_string,
+ StratifiedKFold, 0)
+ assert_raise_message(ValueError, error_string,
+ StratifiedKFold, 1)
 
  # When n_folds is not integer:
  assert_raises(ValueError, KFold, 1.5)

sklearn/tests/test_cross_validation.py

@@ -19,6 +19,7 @@
 from sklearn.utils.testing import assert_array_almost_equal
 from sklearn.utils.testing import assert_array_equal
 from sklearn.utils.testing import assert_warns_message
+from sklearn.utils.testing import assert_raise_message
 from sklearn.utils.testing import ignore_warnings
 from sklearn.utils.mocking import CheckingClassifier, MockDataFrame
 
@@ -160,7 +161,7 @@ def test_kfold_valueerrors():
 
  # Check that a warning is raised if the least populated class has too few
  # members.
- y = [3, 3, -1, -1, 2]
+ y = [3, 3, -1, -1, 3]
 
  cv = assert_warns_message(Warning, "The least populated class",
  cval.StratifiedKFold, y, 3)
@@ -170,11 +171,21 @@ def test_kfold_valueerrors():
  # side of the split at each split
  check_cv_coverage(cv, expected_n_iter=3, n_samples=len(y))
 
+ # Check that errors are raised if all n_labels for individual
+ # classes are less than n_folds.
+ y = [3, 3, -1, -1, 2]
+
+ assert_raises(ValueError, cval.StratifiedKFold, y, 3)
+
  # Error when number of folds is <= 1
  assert_raises(ValueError, cval.KFold, 2, 0)
  assert_raises(ValueError, cval.KFold, 2, 1)
- assert_raises(ValueError, cval.StratifiedKFold, y, 0)
- assert_raises(ValueError, cval.StratifiedKFold, y, 1)
+ error_string = ("k-fold cross validation requires at least one"
+ " train / test split")
+ assert_raise_message(ValueError, error_string,
+ cval.StratifiedKFold, y, 0)
+ assert_raise_message(ValueError, error_string,
+ cval.StratifiedKFold, y, 1)
 
  # When n is not integer:
  assert_raises(ValueError, cval.KFold, 2.5, 2)