#get the feature columns
features = BIOGRAPHIC_DATA_FOR_MERCHANT_CLASSIFICATION_ENCODED.loc[:,'FEATURE_1':'FEATURE_5']
#get the class columns
lables = BIOGRAPHIC_DATA_FOR_MERCHANT_CLASSIFICATION_ENCODED.loc[:,'CLASS']

sm = SMOTE(random_state=12, ratio = 'all', kind='regular', k_neighbors = 5, m_neighbors = 5)
features, lables = sm.fit_sample(features, lables)