3.knn-数据分割-留出法，交叉验证法和自助法

留出法

from sklearn.model_selection import train_test_split
x_train,x_test,y_train,y_test = train_test_split(x,y,random_state=2,test_size=0.25)

from sklearn.model_selection import LeaveOneOut
# 留一法
data = [1,2,3,4]
loo = LeaveOneOut()
for train,test in loo.split(data):
        print("%s %s" % (train,test))

交叉验证法

import numpy as np
from sklearn.model_selection import KFold,StratifiedKFold
x = np.array([
    [1,2,3,4],
    [11,12,13,14],
    [21,22,23,24],
    [31,32,33,34],
    [41,42,43,44],
    [51,52,53,54],
    [61,62,63,64],
    [71,72,73,74]
])

y = np.array([1,1,0,0,1,1,0,0])

print("KFold")
folder = KFold(n_splits=4,random_state=0,shuffle=False)
for train,test in folder.split(x,y):
    print("train:%s,test:%s" % (train,test))

print("StratifiedKFold")
sfolder = StratifiedKFold(n_splits=4,random_state=0,shuffle=False)
for train,test in sfolder.split(x,y):
    print("train:%s,test:%s" % (train,test))

自助法

总结