利用sklearn实现简单的KNN

#sklearn 分类器的学习import numpy as npfrom sklearn import datasetsfrom sklearn.cross_validation import train_test_splitfrom sklearn.neighbors import KNeighborsClassifier#利用KNN实现分类#这里导入了花的数据iris = datasets.load_iris()iris_X = iris.datairis_Y = iris.targetprint(iris_X[:2,:])print(iris_Y)#展示一下数据的形式#将数据分成测试集和训练集，测试集占百分之三十,并对数据进行shuffleX_train,X_test,Y_train,Y_test = train_test_split(iris_X,iris_Y,test_size=0.3)knn = KNeighborsClassifier()knn.fit(X_train,Y_train)#利用knn去预测print(knn.predict(X_test))#显示数据的实际值print(Y_test)