locat.rgmm.compute_loss(X, pi, mu, sigma, membership_weight)

locat.rgmm.e_step(X, pi, mu, sigma)

locat.rgmm.hardbootstrap_gmm(X, raw_weights, n_components, fraction, n_inits=30, reg_covar=0.0, seed=1)

fraction: what proportion of items to sample

locat.rgmm.rgmm(X, weights, n_components, n_inits, reg_covar, true_weights=None)

locat.rgmm.simplebootstrap_gmm(X, n_components, fraction, n_inits=30, reg_covar=0.0, seed=1)

fraction: what proportion of items to sample

locat.rgmm.softbootstrap_gmm(X, raw_weights, n_components, n_inits=100, reg_covar=0.0, seed=1, buckets=None)

locat.rgmm.train_em(X, samples_weights, mu_init, sigma_init, n_components, n_inits=25, reg_covar=0.0, rtol=1e-06, max_iter=500, seed=1)

locat.rgmm.weighted_gmm_init(X, w, n_c, n_inits)

locat.rgmm.weighted_m_step(X, membership_weight, sample_weights, reg_covar)