정부의 교육과 주거 지원 정책: 혜택과 활용 방법
def f(x): return np.sin((x-3)**2) + 0.5*np.cos(6*(x-4)) # Generate samples between -1 and 7 (exclusive) x_samples = np.linspace(-1, 7, 1000) y_samples = f(x_samples) # Add noise to the function values noise_level = 0.2 y_noisy_samples = y_samples + noise_level * np.random.normal(size=x_samples.shape) # Plot the true function and noisy data points plt.figure(figsize=(10, 6)) plt.plot(x_samples, f(x_samples), label=’True Function’, color=’black’) … Read more