object = TopicModel: Compute the log-likelihood of a "TopicModel" object. For "VEM" objects the sum of the log-likelihood of all documents given the parameters for the topic distribution and for the word distribution of each topic is approximated using the variational parameters and underestimates the log-likelihood by the Kullback-Leibler divergence between the variational posterior probability and the true posterior
对象= TopicModel:计算对数似然的"TopicModel"对象。对于"VEM"对象的所有文件的主题分布,每一个主题的单词分布的参数对数似然的总和近似的Kullback-Leibler散度的变参数,低估了对数似然之间的变化后验概率,真正的后
object = Gibbs_list: Compute the log-likelihoods of the "TopicModel" objects contained in the "Gibbs_list"
对象= Gibbs_list:计算对数似然"TopicModel"对象包含在"Gibbs_list"