补全代码生成一个多项式回归曲线 并对代码进行简单的注释

Question

import numpy as np
import os
import matplotlib
import matplotlib.pyplot as plt
plt.rcParams['axes.labelsize'] = 14
plt.rcParams['xtick.labelsize'] = 12
plt.rcParams['ytick.labelsize'] = 12
np.random.seed(42)
import warnings
warnings.filterwarnings('ignore')

x = 2np.random.uniform(-3, 3, size=100)
X = x.reshape(100, 1)
y = 0.5X**2+X+np.random.randn(100,1)

plt.scatter(x, y)
plt.axis([-3,3,-10,10])
plt.show()

X_poly = np.hstack([X, X**2])

补全代码生成一个多项式回归曲线 并对上述各行代码进行简单的注释

Answer 1

你题目的解答代码如下：

import numpy as np
import os
import matplotlib
import matplotlib.pyplot as plt
plt.rcParams['axes.labelsize'] = 14
plt.rcParams['xtick.labelsize'] = 12
plt.rcParams['ytick.labelsize'] = 12
np.random.seed(42)
import warnings
warnings.filterwarnings('ignore')

x = 2*np.random.uniform(-3, 3, size=100)
X = x.reshape(100, 1)
y = 0.5*X**2+X+np.random.randn(100,1)

plt.scatter(x, y)
plt.axis([-3,3,-10,10])

X_poly = np.hstack([X, X**2])


from sklearn.linear_model import LinearRegression

lin_reg = LinearRegression()
lin_reg.fit(X_poly, y)
y_predict = lin_reg.predict(X_poly)

# 由于x是乱的，所以应该进行排序
plt.plot(np.sort(x), y_predict[np.argsort(x)], color='r')
plt.show()