python - 类型错误 : gradientDesc() takes exactly 1 argument (4 given)

Question

尝试在 Python 中实现逻辑回归:

下面是成本函数:

def costFunction(theta_array):
   m = len(X1)
   theta_matrix = np.transpose(np.mat(theta_array))

   H_x = 1 / (1 + np.exp(-X_matrix * theta_matrix))
   J_theta = ((sum(np.multiply((-Y_matrix), np.log(H_x)) - np.multiply((1 - Y_matrix), np.log(1 - H_x)))) / m )[0, 0]

   return J_theta

下面是梯度函数:

def gradientDesc(theta_tuple):
   theta_matrix = np.transpose(np.mat(theta_tuple))

   H_x = 1 / (1 + np.exp(-X_matrix * theta_matrix))
   G_theta0 = (sum(np.multiply(H_x - Y_matrix, X_matrix[:, 0])) / m)[0, 0]
   G_theta1 = (sum(np.multiply(H_x - Y_matrix, X_matrix[:, 1])) / m)[0, 0]
   G_theta2 = (sum(np.multiply(H_x - Y_matrix, X_matrix[:, 2])) / m)[0, 0]


   return np.array((G_theta0, G_theta1, G_theta2))

然后我运行optimize.fmin_bfgs函数，如下所示:

initial_theta = np.zeros((3, 1))
theta_tuple = (0, 0, 0)

theta_optimize = op.fmin_bfgs(costFunction, initial_theta, gradientDesc, args = (theta_tuple))

然后我收到以下错误:

**TypeError: gradientDesc() takes exactly 1 argument (4 given)**

谁能告诉我如何解决？ :)谢谢!

Answer 1

对于 args 参数，您应该使用逗号指定单项元组(也称为 singleton )；否则括号只会对表达式进行分组。

更改:

theta_optimize = op.fmin_bfgs(costFunction, initial_theta, gradientDesc, args = (theta_tuple))

至:

theta_optimize = op.fmin_bfgs(costFunction, initial_theta, gradientDesc, args = (theta_tuple,))

此外，您的gradientDesc 应该接受每个 documentation 的附加参数。 .

更改:

def gradientDesc(theta_tuple):

至:

def gradientDesc(x, theta_tuple):