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Results tagged with smote
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Synthetic Minority Oversampling Technique (SMOTE) is an approach used for dealing with imbalanced datasets before running them through machine learning models.
1
vote
Solving multi-class imbalance classification using smote and OSS
Using the SMOTE/SMOTEENN libraries in Python, you can oversample/undersample all of the classes in one line of code. … Also, if you have categorical features in your feature set, you may need to take a look at SMOTE-NC approach too, as SMOTE and SMOTEENN are purely distance-based and underestimate the role and value of …
- 611
5
votes
Accepted
Combining 'class_weight' with SMOTE
I tried different classifiers using a combination of SMOTE and class_weight, the results are almost the same as using only the SMOTE approach, and this new config made almost no difference (which could …
- 611