朴素贝叶斯分类器(伯努利贝叶斯+高斯贝叶斯+多项式贝叶斯)
1 from sklearn.datasets import load_diabetes 2 X,y=load_diabetes().data,load_diabetes().target 3 X_train,X_test,y_train,y_test=train_test_split(X,y,random_state=8) 4 lr=LinearRegression().fit(X_train,y_train) 5 print("the coefficient:{}".format(lr.coef_)) 6 print('the intercept:{}'.format(lr.intercept_)) 7 print("the score of this model:{:.3f}".format(lr.score(X_test,y_test))) 1 import matplotlib.pyplot as plt 2 plt.scatter(X[:,0],X[:,1],c=y,cmap=plt.cm.spring,edgecolors='k') 3 plt.show() 1 #伯努利贝叶斯分类器 2 from sklearn.naive_bayes import BernoulliNB 3 bnb=BernoulliNB() 4 bnb.fit(X_train,y_train)