Python机器学习库SKLearn分类算法之朴素贝叶斯

参考地址：http://scikit-learn.org/stable/modules/naive_bayes.html

http://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.GaussianNB.html#sklearn.naive_bayes.GaussianNB

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()
clf.fit(X, Y)       //训练数据
print(clf.predict([[-0.8, -1]])) //预测
clf_pf = GaussianNB()
clf_pf.partial_fit(X, Y, np.unique(Y)) //增加一部分样本
print(clf_pf.predict([[-0.8, -1]]))