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))