iter

Author: glemaitre

imblearn/misc.py

@@ -43,10 +43,11 @@ class FunctionSampler(SamplerMixin):
 
     Examples
     --------
-    >>> from sklearn.datasets import fetch_mldata
+    >>> from sklearn.datasets import make_classification
     >>> from imblearn.misc import FunctionSampler
-    >>> pima = fetch_mldata('diabetes_scale')
-    >>> X, y = pima['data'], pima['target']
+    >>> X, y = make_classification(n_classes=2, class_sep=2,
+    ... weights=[0.1, 0.9], n_informative=3, n_redundant=1, flip_y=0,
+    ... n_features=20, n_clusters_per_class=1, n_samples=1000, random_state=10)
 
     We can create to select only the first ten samples for instance.
 
@@ -71,7 +72,7 @@ class FunctionSampler(SamplerMixin):
     >>> X_res, y_res = sampler.fit_sample(X, y)
     >>> print('Resampled dataset shape {}'.format(
     ...     sorted(Counter(y_res).items())))
-    Resampled dataset shape [(-1, 268), (1, 268)]
+    Resampled dataset shape [(0, 100), (1, 100)]
 
     """