import numpy as np
from sklearn.naive_bayes import BernoulliNB

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

# 有风-潮湿-多云-闷热
y = np.array([1, 1, 1, 1, 0, 1, 0, 1, 1, 0])
bnb = BernoulliNB()
bnb.fit(x, y)
day_pre = [[1, 0, 1, 0]]
pre = bnb.predict(day_pre)
print("预测结果如下:\n", "*" * 50)
print("结果为: ", pre)
print("*" * 50)

# 进一步查看概率分析
pre_pro = bnb.predict_proba(day_pre)
print("不下雨的概率为: ", pre_pro[0][0], "\n下雨的概率为: ", pre_pro[0][1])