Created
January 15, 2021 02:38
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0004_OLSregression(2)
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from pylab import plt | |
import numpy as np | |
def f(x): | |
return 3 * x ** 3 - 4 * x ** 2 | |
x = np.linspace(-2, 4, 25) | |
y = f(x) | |
plt.figure(figsize=(10, 6)) | |
a, b = np.polyfit(x, y, 1) | |
y_hat = a*x + b | |
a, b, c = np.polyfit(x, y, 2) | |
y_hat2 = a*x**2 + b*x + c | |
a, b, c, d = np.polyfit(x, y, 3) | |
y_hat3 = a*x**3 + b*x**2 + c*x + d | |
a, b, c, d, e = np.polyfit(x, y, 4) | |
y_hat4 = a*x**4 + b*x**3 + c*x**2 + d*x + e | |
plt.plot(x, y_hat, 'b-', label='degree=1'); | |
plt.plot(x, y_hat2, 'y-', label='degree=2'); | |
plt.plot(x, y_hat3, 'g-', label='degree=3'); | |
plt.plot(x, y_hat4, 'o-', label='degree=4'); | |
plt.plot(x, y, 'ro', label='Test data'); | |
plt.legend(); |
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