smote_var.py

# printing the number of samples before smote

print('majority class: %d' % np.sum(y == 0))
print('minority class: %d' % np.sum(y == 1))

#majority class: 100
#minority class: 50

#The oversampling is carried out by instantiating any oversampler implemented in the package and calling the sample function.
oversampler= sv.distance_SMOTE()
X_samp, y_samp= oversampler.sample(X, y)

# printing the number of samples
print('majority class: %d' % np.sum(y_samp == 0))
print('minority class: %d' % np.sum(y_samp == 1))

#majority class: 100
#minority class: 100