def output_mean_square_mean_error(self, path, k=1):
        if k > 1:
            step = len(self.errors) / k
            errors = np.zeros(step)

            for i in xrange(0, len(self.errors), step):
                error_run = []

                for j in range(i, i + step):
                    error_run.append(self.errors[j])

                errors = [sum(x) for x in zip(errors, error_run)]

            errors = [k / x for x in errors]
        else:
            errors = self.errors

        self.view.plot_data("Training", [errors], "Epoch", "Mean square error")
        self.view.show()
        self.view.save(path)
dataset/ETHPy150Open tonybeltramelli/Deep-Spying/server/analytics/modules/classification/RelevanceAssessment.py/RelevanceAssessment.output_mean_square_mean_error/swapped operands of `/`