This repository was archived by the owner on Jul 13, 2023. It is now read-only.
This repository was archived by the owner on Jul 13, 2023. It is now read-only.
Use Borderline SMOTE to deal with the problem of sample imbalance #150
Description
Why only two of these categories have been sample balanced？
from imblearn.over_sampling import BorderlineSMOTE
nn_k = NearestNeighbors(n_neighbors=29)
bsmote = BorderlineSMOTE(random_state=42,k_neighbors=nn_k)
X_train_smote,y_train_smote = bsmote.fit_resample(X_train,y_train)
print(sorted(Counter(y_train_smote).items()))
result：[(0, 136), (1, 136), (2, 3)]