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Hi! First off, I know very little about machine learning in general, and imbalanced machine learning in particular, so I don't know if this will make much sense.
Steps/Code to Reproduce
import numpy as np from imblearn.combine import SMOTETomek from imblearn.over_sampling import SVMSMOTE sampler = SMOTETomek(smote=SVMSMOTE()) sampler.fit_resample(np.arange(10).reshape(5, -1), np.arange(5))
A SMOTETomek sampler that uses SVMSMOTE for oversampling.
PS. Is there any particular reason why ADASYN wouldn't work in this context?
Ah ok :)