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21 lines
545 B
21 lines
545 B
import numpy as np
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import matplotlib.pyplot as plt
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###############################
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#Datos originales
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###############################
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X = 2 * np.random.rand(100, 1)
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y = 4 + 3 * X + np.random.randn(100,1)
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plt.plot(X,y,".")
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###############################
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X_b = np.c_[np.ones((100,1)), X] #Se agrega x0=1 para cada instancia
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eta = 0.1 #Pasos
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n_itera = 1000
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m=100
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theta = np.random.randn(2,1) #Inicialización aleatoria
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for iteracion in range (n_itera):
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gradiente = 2/m * X_b.T.dot(X_b.dot(theta)-y)
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theta = theta - eta * gradiente
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print(theta)
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