iter

Author: glemaitre

doc/miscellaneous.rst

@@ -17,6 +17,7 @@ a single function. Additional parameters can be added using the attribute
 ``kw_args`` which accepts a dictionary. The following example illustrates how
 to retain the 10 first elements of the array ``X`` and ``y``::
 
+  >>> import numpy as np
   >>> from imblearn.misc import FunctionSampler
   >>> from sklearn.datasets import make_classification
   >>> X, y = make_classification(n_samples=5000, n_features=2, n_informative=2,
@@ -28,9 +29,9 @@ to retain the 10 first elements of the array ``X`` and ``y``::
   ...   return X[:10], y[10:]
   >>> sampler = FunctionSampler(func=func)
   >>> X_res, y_res = sampler.fit_sample(X, y)
-  >>> (X_res == X[:10]).all()
+  >>> np.all(X_res == X[:10])
   True
-  >>> (y_res == y_res[:10]).all()
+  >>> np.all(y_res == y_res[:10])
   True
 
 We illustrate the use of such sampler to implement an outlier rejection