请教线性回归代码问题

新手小白刚刚开始接触机器学习，写了一个线性回归的代码，但是跑出来的结果一直不对，黔驴技穷了，求大佬指点

class LinearRegression:

    def read_data(self):
        data = np.genfromtxt("data.csv", delimiter=',')
        x_num = data.shape[1] - 1
        data_num = data.shape[0]
        bais = np.ones(data_num).reshape((data_num, 1))
        x = data[:, 0 : x_num].reshape((data_num, x_num))
        x = np.concatenate((bais, x), axis=1)
        y = data[:, -1].reshape((data_num, 1))
        return data, x, y

    def generate_parameter(self, x_num):
        parameter = np.zeros((x_num, 1))
        return parameter

    def compute_cost(self, x, y, parameter):
        tmp = np.dot(x, parameter) - y
        return 0.5 * float(np.dot(np.transpose(tmp), tmp))

    def gradient_descent(self, x, y, parameter, lr):
        tmp = np.dot(x, parameter) - y
        gradient = np.dot(np.transpose(x), tmp)
        parameter_updated = parameter - lr * gradient
        return parameter_updated

    def train_model(self, x, y, parameter, lr, iteration):
        cost_list = []
        para_tmp = parameter
        for i in range(iteration):
            cost_list.append(self.compute_cost(x, y, para_tmp))
            para_tmp = self.gradient_descent(x, y, para_tmp, lr)
        return para_tmp, cost_list