classification dataset 分类数据集

import numpy as np
X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
Y = np.array([1, 1, 1, 2, 2, 2])
from sklearn.naive_bayes import GaussianNB
clf = GaussianNB()
#拟合数据
clf.fit(X, Y)
print("==Predict result by predict==")
print(clf.predict([[-0.8, -1]]))
print("==Predict result by predict_proba==")
print(clf.predict_proba([[-0.8, -1]]))
print("==Predict result by predict_log_proba==")
print(clf.predict_log_proba([[-0.8, -1]]))

朴素贝叶斯的三个常用模型：高斯、多项式、伯努利

import numpy as np

class MultinomialNB(object):

    def