我已经为非正则逻辑回归成本函数和寻找梯度编写了一些代码，但是无论我尝试什么，我的代码都会不断返回相同的TypeError。

我已经尝试过对代码进行矢量化和for循环实现，但没有任何效果。我还要指出的是，评分者总是对我的成本函数进行满分评分，而不是对偏导数进行查找的代码。我的结果始终符合预期的费用，但渐变部分没有任何回报。

它说这是成本： J（?）= 1?∑? =1?[-?（?）log（ℎ?（?（?）））-（1-?（?））log（1-ℎ?（?（?）））] >

这是偏导数： ∂?（?）∂?? = 1?∑? =1?（ℎ?（?（?））−?（?））?（?）?

（通过本课程的学习，我可以验证这是正确的）

def costFunction(theta,X,y):
    # Initialize some useful values
    m = y.size  # number of training examples

    # You need to return the following variables correctly 
    J = 0
    grad = np.zeros(theta.shape)

    # ====================== YOUR CODE HERE ============
    for i in range(m):
        hypothesis = sigmoid(np.dot(theta.T,X[i,:]))
        J += y[i] * math.log(hypothesis) + (1 - y[i]) * math.log(1 - hypothesis)
        for j in range(n):
            grad = (hypothesis - y[i]) * X[i,j]

    J = (-1 / m) * J
    grad = (1 / m) * grad
    # =============================================================
    return J,grad



# Initialize fitting parameters
initial_theta = np.zeros(n+1)

cost,grad = costFunction(initial_theta,y)

print('Cost at initial theta (zeros): {:.3f}'.format(cost))
print('Expected cost (approx): 0.693\n')

print('Gradient at initial theta (zeros):')
#print('\t[{:.4f},{:.4f},{:.4f}]'.format(*grad))
print('Expected gradients (approx):\n\t[-0.1000,-12.0092,-11.2628]\n')

# Compute and display cost and gradient with non-zero theta
test_theta = np.array([-24,0.2,0.2])
cost,grad = costFunction(test_theta,y)

print('Cost at test theta: {:.3f}'.format(*cost))
print('Expected cost (approx): 0.218\n')

print('Gradient at test theta:')
print('\t[{:.3f},{:.3f},{:.3f}]'.format(*grad))
print('Expected gradients (approx):\n\t[0.043,2.566,2.647]')

我希望输出为：

Cost at initial theta (zeros): 0.693
Expected cost (approx): 0.693

Gradient at initial theta (zeros):
    [-0.1000,-11.2628]
Expected gradients (approx):
    [-0.1000,-11.2628]

但是我得到以下信息：

Cost at initial theta (zeros): 0.693
Expected cost (approx): 0.693

Gradient at initial theta (zeros):
Expected gradients (approx):
    [-0.1000,-11.2628]

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-35-ab2a7b541269> in <module>()
     15 cost,y)
     16 
---> 17 print('Cost at test theta: {:.3f}'.format(*cost))
     18 print('Expected cost (approx): 0.218\n')
     19 

TypeError: format() argument after * must be an iterable,not numpy.float64