Comments (1)
pintub
commented on July 24, 2024
𝐽(𝜃)'s regularization part is sum of j=1 to n, so 1st theta parameter (theta0) is not penalized . You should use thetaZero for J calculation .
def costFunctionReg(theta, X, y, lambda_):
m, n = X.shape
theta = theta.reshape((n, 1))
h_theta = sigmoid(X @ theta)
thetaZero = theta
thetaZero[1] = 0
J = (1 / m) * (-y.T @ numpy.log(h_theta) - (1 - y).T @ numpy.log(1 - h_theta)) + (lambda_ / (2 * m)) * (theta[1:thetaZero.size]).T @ theta[1:thetaZero.size]
grad = ((1 / m) * (h_theta - y).T @ X) + lambda_ / m * thetaZero.T
grad = grad.reshape((n, 1))
return J, grad
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