交叉严重 crossvalidation

交叉只是做验证，让不至于过拟合，次数一般自己来定

# -*- coding:utf-8 -*-
from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
from sklearn.model_selection import cross_val_score#引入交叉验证
import  matplotlib.pyplot as plt
###引入数据###
iris=datasets.load_iris()
X=iris.data
y=iris.target
###设置n_neighbors的值为1到30,通过绘图来看训练分数###
k_range=range(1,31)
k_score=[]
for k in k_range:
    knn=KNeighborsClassifier(n_neighbors=k)
    scores=cross_val_score(knn,X,y,cv=10,scoring='accuracy')#for classfication
    k_score.append(scores.mean())
plt.figure()
plt.plot(k_range,k_score)
plt.xlabel('Value of k for KNN')
plt.ylabel('CrossValidation accuracy')
plt.show()