pgm_Bayesian_Network_fundamentals
2015-12-02 19:45
253 查看
A Bayesian network is :
a) A directed acyclic graph (DAG) G, which nodes represent the variables X1,...,Xn. (有向无环图,每个结点表示变量)
b) for each node Xi, a CPD P(Xi|ParG(Xi)) is assigned. ParG(Xi) 表示 图中Xi 的双亲结点. CPD: Conditional Probability Distribution;但是某些无入边的结点(即没有父结点)的CPD可能就是其概率分布。
一个Bayesian Network 表示一个 joint distribution ,via chain rule for the BN:
P(X1,...,Xn) = ∏iP(Xi|ParG(Xi)) ; note that BN is a legal Distribution : i.e., ΣP = 1.
定义 P factorizes over G:
Let G be a graph over X1,...Xn, P factorizes over G if P(X1,...,Xn) = ∏iP(Xi|ParG(Xi))
3 types of Reasoning:
a) Causal Reasoning : reasoning from up to bottom. (沿着有向边的指向进行的reasoning)
b) Evidential Reasoning: bottom-up.
c) InterCausal reasoning: reasoning between two causes of a single effects. (V-structure)
Influence 的概念(理解的不好,还要重新再看一下):Y influence X for that: condition on Y change the Beliefs about X. 即基于Y的观测会改变我们对X的分布的认识.
V-structure 的概念: X-->Z<--Y 在没有evidence 的情况下,X无法影响到Y。即X,Y之间无法形成一条active trail。
Active Trail的概念: A trail X1...Xn is active given Z if:
1) for any Xi-1-->Xi<--Xi+1 ; we have that Xi or any of its descendents belong to Z ;
2) no other Xi in Z
也就是说在一个trail里面,对任意的V-structure Xi-1-->Xi<--Xi+1, Xi必须可以被观察到,且Xi 及其descendents之多只有一个被观测到。
***************************************************************************************************************************
Independency & Factorization
a Joint distribution P(X,Y,Z) is proportion to Φ1(X,Z)*Φ2(Y,Z) ,Then (X is independent on Y |Z)
也就是说对一个分布P 进行factorize 的过程 揭示了分布P中的变量之间的independencies。
d-separated 的定义:
X and Y are d-separated in G given Z if : there is no active trail in G between X and Y given Z : d-sepG(X,Y|Z)
定理: If P factorizes over G, and d-sepG(X,Y|Z), then P sattisfies (X is independent on Y|Z).
推论: Any node is d-separated from its non-descendents given its parents.
(*) If P factorizes over G, then in P, any variables is independent of its non-descendents given its parents.
***************************************************************************************************************************
I-maps (Independency Map)
I(G) = {(X is independent of Y|Z):d-sepG(X,Y|Z)} 如果P 满足上式, 那么G 就是P的一个I—map。
而 P factorizes over G <==> G is an I-map for P
a) A directed acyclic graph (DAG) G, which nodes represent the variables X1,...,Xn. (有向无环图,每个结点表示变量)
b) for each node Xi, a CPD P(Xi|ParG(Xi)) is assigned. ParG(Xi) 表示 图中Xi 的双亲结点. CPD: Conditional Probability Distribution;但是某些无入边的结点(即没有父结点)的CPD可能就是其概率分布。
一个Bayesian Network 表示一个 joint distribution ,via chain rule for the BN:
P(X1,...,Xn) = ∏iP(Xi|ParG(Xi)) ; note that BN is a legal Distribution : i.e., ΣP = 1.
定义 P factorizes over G:
Let G be a graph over X1,...Xn, P factorizes over G if P(X1,...,Xn) = ∏iP(Xi|ParG(Xi))
3 types of Reasoning:
a) Causal Reasoning : reasoning from up to bottom. (沿着有向边的指向进行的reasoning)
b) Evidential Reasoning: bottom-up.
c) InterCausal reasoning: reasoning between two causes of a single effects. (V-structure)
Influence 的概念(理解的不好,还要重新再看一下):Y influence X for that: condition on Y change the Beliefs about X. 即基于Y的观测会改变我们对X的分布的认识.
V-structure 的概念: X-->Z<--Y 在没有evidence 的情况下,X无法影响到Y。即X,Y之间无法形成一条active trail。
Active Trail的概念: A trail X1...Xn is active given Z if:
1) for any Xi-1-->Xi<--Xi+1 ; we have that Xi or any of its descendents belong to Z ;
2) no other Xi in Z
也就是说在一个trail里面,对任意的V-structure Xi-1-->Xi<--Xi+1, Xi必须可以被观察到,且Xi 及其descendents之多只有一个被观测到。
***************************************************************************************************************************
Independency & Factorization
a Joint distribution P(X,Y,Z) is proportion to Φ1(X,Z)*Φ2(Y,Z) ,Then (X is independent on Y |Z)
也就是说对一个分布P 进行factorize 的过程 揭示了分布P中的变量之间的independencies。
d-separated 的定义:
X and Y are d-separated in G given Z if : there is no active trail in G between X and Y given Z : d-sepG(X,Y|Z)
定理: If P factorizes over G, and d-sepG(X,Y|Z), then P sattisfies (X is independent on Y|Z).
推论: Any node is d-separated from its non-descendents given its parents.
(*) If P factorizes over G, then in P, any variables is independent of its non-descendents given its parents.
***************************************************************************************************************************
I-maps (Independency Map)
I(G) = {(X is independent of Y|Z):d-sepG(X,Y|Z)} 如果P 满足上式, 那么G 就是P的一个I—map。
而 P factorizes over G <==> G is an I-map for P
相关文章推荐
- bootstrap快速链接
- 数字图像处理:第十二章 小波变换
- DataSource 的理解
- 1045. Favorite Color Stripe (30) 简单动态规划(LCS的变形)
- jQuery中ready与load事件的区别
- Java的注释说明
- 给Java程序猿们推荐一些值得一看的好书
- 轻松学习JavaScript九:JavaScript对象和数组
- 脚本删除指定N天前的文件
- bzoj1185[HNOI2007]最小矩形覆盖
- HDC与HWND的关系
- spatialhadoop2.3源码阅读(四) FileMBR类
- 前端--关于css选择器
- C语言开发总结(十九)
- 使用JavaScript实现一个“字节码解释器”,并用它重新实现JS科学计算器的后端(后续1)
- 如果有一天: 你不再寻找爱情,只是去爱;你不再渴望成功,只是去做;你不再追求成长,只是去修;一切才真正开始! —— 纪伯伦
- Android进程和线程 --消息队列模型 (Looper, MessageQueue, Handler) (1)
- Java在Web开发语言上败给了PHP
- 【十大经典数据挖掘算法】C4.5
- 旅行销售员问题-------分支限界法