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lines changed Original file line number Diff line number Diff line change @@ -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
You can’t perform that action at this time.
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