from sklearn.naive_bayes import GenerativeBayes, GaussianNB
from sklearn.datasets import make_blobs
import numpy as np

for N in [100, 10000, 1000000]:
    for dim in (1, 5):
        for classes in (2, 6):
            X, y = make_blobs(N, dim, centers=classes)
            print
            print "shape = ({0}, {1}), {2} classes".format(N, dim, classes)
            print "GenerativeBayes"
            %timeit GenerativeBayes('normal_approximation').fit(X, y).predict(X)
            print "GaussianNB"
            %timeit GaussianNB().fit(X, y).predict(X)