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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
88
99We previously presented :class: `SMOTE ` and showed that this method can generate
1010noisy samples by interpolating new points between marginal outliers and
11- inliers. This issue can be solved by cleaning the resulted space obtained
12- after over-sampling.
11+ inliers. This issue can be solved by cleaning the space resulting
12+ from over-sampling.
1313
1414.. currentmodule :: imblearn.combine
1515
1616In this regard, Tomek's link and edited nearest-neighbours are the two cleaning
17- methods which have been added pipeline after SMOTE over-sampling to obtain a
18- cleaner space. Therefore, imbalanced-learn implemented two ready-to- use class
19- which pipeline both over- and under-sampling methods: (i) :class: `SMOTETomek `
17+ methods that have been added to the pipeline after applying SMOTE over-sampling
18+ to obtain a cleaner space. The two ready-to use classes imbalanced-learn implements
19+ for combining over- and undersampling methods are : (i) :class: `SMOTETomek `
2020and (ii) :class: `SMOTEENN `.
2121
22- These two classes can be used as any other sampler with identical parameters
23- than their former samplers::
22+ Those two classes can be used like any other sampler with parameters identical
23+ to their former samplers::
2424
2525 >>> from collections import Counter
2626 >>> from sklearn.datasets import make_classification
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