At last , it can obtain the posterior probability distibution of each unlabelled classes by analysing these stochastic data . it is easy to get a stochastic sample that satisfies some special distribution through running a special markov chain , so mcmc ( markov chain monte carlo ) is the most common monte carlo bayesian method 運(yùn)行一個(gè)特定的馬爾可夫鏈可以容易地獲得滿足某個(gè)特定分布的隨機(jī)抽樣,所以馬爾可夫鏈蒙特卡羅( mcmc )是最常用的蒙特卡羅貝葉斯分類方法。