sklearn实现knn

 1 #sklearn实现KNN
 2 步骤：
 3     1、导入分类器
 4     2、加载数据集
 5     3、分割训练数据、测试数据
 6     4、用分类器拟合数据
 7     5、预测数据
 8 
 9 from sklearn import datasets
10 from sklearn.model_selection import train_test_split
11 from sklearn.neighbors import KNeighborsClassifier
12 
13 #创建数据
14 iris=datasets.load_iris()
15 iris_X=iris.data
16 iris_Y=iris.target
17 print(iris_X[:5,:])
18 print(iris_Y[:5])
19 
20 X_train,X_test,y_train,y_test=train_test_split(iris_X,iris_Y,test_size=0.3)
21 print(y_train)
22 
23 knn=KNeighborsClassifier()
24 knn.fit(X_train,y_train)
25 print(knn.predict(X_test))
26 print(y_test)

 <iframe src="http://nbviewer.jupyter.org/github/LiaoPan/MyCodeSpace/blob/master/Demo_juypter.ipynb" width="850" height="500"></iframe>

转载于:https://www.cnblogs.com/aqiliangxue/p/8678277.html

来源：CSDN

作者：weixin_30815427

链接：https://blog.csdn.net/weixin_30815427/article/details/98283107