import numpy as np
from sklearn.naive_bayes import GaussianNB
train_x=np.array(
        [[0.697, 0.460],
        [0.774, 0.376],
        [0.634, 0.264],
        [0.608, 0.318],
        [0.556, 0.215],
        [0.403, 0.237],
        [0.481, 0.149],
        [0.437, 0.211],

        [0.666, 0.091],
        [0.243, 0.267],
        [0.245, 0.057],
        [0.343, 0.099],
        [0.639, 0.161],
        [0.657, 0.198],
        [0.360, 0.370],
        [0.593, 0.042],
        [0.719, 0.103]])

train_y=np.array([1, 1, 1, 1, 1, 1, 1, 1,  0, 0, 0, 0, 0, 0, 0, 0, 0])

gnb= GaussianNB()
gnb.fit(train_x, train_y)
print(gnb.predict([[0.697,0.460]]))