机器学习—K近邻

一、算法原理

还是图片格式~

 

二、sklearn实现

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
import seaborn as sns
mpl.rcParams['font.sans-serif'] = [u'SimHei']
mpl.rcParams['axes.unicode_minus'] = False
from sklearn.datasets import load_digits
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
from sklearn.neighbors import KNeighborsClassifier
from sklearn.model_selection import GridSearchCV

digits = load_digits()
x_data = digits.data
y_data = digits.target
x_train,x_test,y_train,y_test = train_test_split(x_data,y_data)
knn = KNeighborsClassifier()
model_knn = GridSearchCV(knn,param_grid=({'n_neighbors':np.arange(1,5)}),cv=10)
model_knn.fit(x_train,y_train)
print(model_knn.best_params_)
y_hat = model_knn.predict(x_test)
print('正确率',accuracy_score(y_hat,y_test))

正确率好高啊，直接用1个k来做。。。
{'n_neighbors': 1}
正确率 0.986666666667