def poisson_consensus_se(data, k, n_runs=<NUM_LIT:10>, **se_params):
clusters = []<EOL>for i in range(n_runs):<EOL><INDENT>assignments, means  = poisson_cluster(data, k)<EOL>clusters.append(assignments)<EOL><DEDENT>clusterings = np.vstack(clusters)<EOL>consensus = CE.cluster_ensembles(clusterings, verbose=False, N_clusters_max=k)<EOL>init_m, init_w = nmf_init(data, consensus, k, '<STR_LIT>')<EOL>M, W, ll = poisson_estimate_state(data, k, init_means=init_m, init_weights=init_w, **se_params)<EOL>return M, W, ll<EOL>
Initializes Poisson State Estimation using a consensus Poisson clustering.