imbalance.py

from collections import Counter

# splitting the data as X and y
X = tel_data_selected.drop('churn', axis=1)
y = tel_data_selected['churn']

# making a SMOTE object
resampler = SMOTE(random_state=5)

# splitting the data into train and test
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, stratify=y)

# resampling the data
X_resampled, y_resampled = resampler.fit_resample(X_train, y_train)

# verifying the resampled data
print('Resampled dataset shape %s' % Counter(y_resampled))