Prior probability（先验概率) Joint probability distribution for a set of random variables gives the probability of every atomic event on those random variables (i.e., every sample point) 联合概率分布给出一个随机变量集的值的全部组合的概率 e.g.,P(Weather,Cavity)=a 4 x 2 matrix of values: Weather sunny rainy doudy snow Cavity true 0.1440.02 0.016 0.02 Cavity =false 0.576 0.08 0.064 0.08 Every question about a domain can be answered by the joint distribution because every event is a sum of sample points 4口◆4⊙t4三1=，￥9QC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Prior probability（先验概率） Joint probability distribution for a set of random variables gives the probability of every atomic event on those random variables (i.e., every sample point) 联合概率分布给出一个随机变量集的值的全部组合的概率 e.g., P(Weather, Cavity) = a 4 × 2 matrix of values: Weather = sunny rainy doudy snow Cavity = true 0.144 0.02 0.016 0,02 Cavity = false 0.576 0.08 0.064 0.08 Every question about a domain can be answered by the joint distribution because every event is a sum of sample points