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DOC Minor rephrasing in the combine doc (scikit-learn-contrib#330)
* minor rephrasing in the combine doc * Update combine.rst
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doc/combine.rst

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@@ -8,19 +8,19 @@ Combination of over- and under-sampling
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We previously presented :class:`SMOTE` and showed that this method can generate
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noisy samples by interpolating new points between marginal outliers and
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inliers. This issue can be solved by cleaning the resulted space obtained
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after over-sampling.
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inliers. This issue can be solved by cleaning the space resulting
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from over-sampling.
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.. currentmodule:: imblearn.combine
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In this regard, Tomek's link and edited nearest-neighbours are the two cleaning
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methods which have been added pipeline after SMOTE over-sampling to obtain a
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cleaner space. Therefore, imbalanced-learn implemented two ready-to-use class
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which pipeline both over- and under-sampling methods: (i) :class:`SMOTETomek`
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methods that have been added to the pipeline after applying SMOTE over-sampling
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to obtain a cleaner space. The two ready-to use classes imbalanced-learn implements
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for combining over- and undersampling methods are: (i) :class:`SMOTETomek`
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and (ii) :class:`SMOTEENN`.
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These two classes can be used as any other sampler with identical parameters
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than their former samplers::
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Those two classes can be used like any other sampler with parameters identical
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to their former samplers::
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>>> from collections import Counter
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>>> from sklearn.datasets import make_classification

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