240720 knn 最近邻

K最邻近（KNN，K-NearestNeighbor）  结果：

其中虚线就是拟合后的模型

# -*- coding: utf-8 -*-
 import numpy as np
 import matplotlib.pyplot as plt
 from sklearn import neighbors# 加载数据
 amplitude = 10
 num_points = 100
 X = amplitude * np.random.rand(num_points, 1) - 0.5 * amplitude# 加噪声
 y = np.sinc(X).ravel() 
 y += 0.2 * (0.5 - np.random.rand(y.size))# 画图
 plt.figure()
 plt.scatter(X, y, s=40, c='k', facecolors='none')
 plt.title('Input data')# 用输入数据的10倍设置网格
 x_values = np.linspace(-0.5*amplitude, 0.5*amplitude, 10*num_points)[:, np.newaxis]# 最近邻 8
 n_neighbors = 8# 训练knn
 knn_regressor = neighbors.KNeighborsRegressor(n_neighbors, weights='distance')
 y_values = knn_regressor.fit(X, y).predict(x_values)# 画图
 plt.figure()
 plt.scatter(X, y, s=40, c='k', facecolors='none', label='input data')
 plt.plot(x_values, y_values, c='k', linestyle='--', label='predicted values')
 plt.xlim(X.min() - 1, X.max() + 1)
 plt.ylim(y.min() - 0.2, y.max() + 0.2)
 plt.axis('tight')
 plt.legend()
 plt.title('K Nearest Neighbors Regressor')plt.show()