def _n_parameters(self):
        ndim = self.means_.shape[1]
        if self.covariance_type == 'full':
            cov_params = self.n_components * ndim * (ndim + 1) / 2.
        elif self.covariance_type == 'diag':
            cov_params = self.n_components * ndim
        elif self.covariance_type == 'tied':
            cov_params = ndim * (ndim + 1) / 2.
        elif self.covariance_type == 'spherical':
            cov_params = self.n_components
        mean_params = ndim * self.n_components
        return int(cov_params + mean_params + self.n_components - 1)
POSTs a form that contains validation errors.
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/mixture/gaussian_mixture.py/GaussianMixture._n_parameters--crossover with--dataset/ETHPy150Open AppScale/appscale/AppServer/lib/django-1.4/tests/regressiontests/views/tests/generic/create_update.py/CreateObjectTest.test_create_article_with_errors