sklearn的简单使用

 import numpy as np
 from sklearn import datasets
 from sklearn.cross_validation import train_test_split
 from sklearn.neighbors import KNeighborsClassifier
 
 #数据载入
 iris = datasets.load_iris()
 iris_X = iris.data
 iris_y = iris.target
 
 #这里的这个打乱不仅仅是取testsize大小分开，而且还是把顺序打乱了
 trainX,testX,trainY,testY = train_test_split(iris_X,iris_y,test_size = 0.3)
 knn = KNeighborsClassifier()
 
 #训练
 knn.fit(trainX,trainY)
 #得到分类结果
 print(knn.predict(testX))
 print(testY)
 #print (iris_y)
 #print ((iris_X.shape))

import numpy as npfrom sklearn import datasetsfrom sklearn.cross_validation import train_test_splitfrom sklearn.neighbors import KNeighborsClassifier
iris = datasets.load_iris()iris_X = iris.datairis_y = iris.target
#这里的这个打乱不仅仅是取testsize大小分开，而且还是把顺序打乱了trainX,testX,trainY,testY = train_test_split(iris_X,iris_y,test_size = 0.3)knn = KNeighborsClassifier()knn.fit(trainX,trainY)print(knn.predict(testX))print(testY)#print (iris_y)#print ((iris_X.shape))