BN Topic Model 中如何判断conditional independence p(x,y|z)
来源:互联网 发布:怎么让淘宝店铺关掉 编辑:程序博客网 时间:2024/06/06 00:34
use the bayes ball method
http://www.cs.ubc.ca/~murphyk/Bayes/bnintro.html
In general, the conditional independence relationships encoded by a Bayes Net are best be explained by means of the “Bayes Ball” algorithm (due to Ross Shachter), which is as follows: Two (sets of) nodes A and B are conditionally independent (d-separated) given a set C if and only if there is no way for a ball to get from A to B in the graph, where the allowable movements of the ball are shown below. Hidden nodes are nodes whose values are not known, and are depicted as unshaded; observed nodes (the ones we condition on) are shaded. The dotted arcs indicate direction of flow of the ball.
The most interesting case is the first column, when we have two arrows converging on a node X (so X is a “leaf” with two parents). If X is hidden, its parents are marginally independent, and hence the ball does not pass through (the ball being “turned around” is indicated by the curved arrows); but if X is observed, the parents become dependent, and the ball does pass through, because of the explaining away phenomenon. Notice that, if this graph was undirected, the child would always separate the parents; hence when converting a directed graph to an undirected graph, we must add links between “unmarried” parents who share a common child (i.e., “moralize” the graph) to prevent us reading off incorrect independence statements.
Now consider the second column in which we have two diverging arrows from X (so X is a “root”). If X is hidden, the children are dependent, because they have a hidden common cause, so the ball passes through. If X is observed, its children are rendered conditionally independent, so the ball does not pass through. Finally, consider the case in which we have one incoming and outgoing arrow to X. It is intuitive that the nodes upstream and downstream of X are dependent iff X is hidden, because conditioning on a node breaks the graph at that point.
- BN Topic Model 中如何判断conditional independence p(x,y|z)
- x > y ? y : x > z ? z : x;
- (X * Y) % Z
- x/y/z轴
- iOS中控件旋转:绕x,y,z轴
- X/Y/Z Modem区别
- z = 16*x + y
- DUMP(w[,x[,y[,z]]])
- 求(x-y+z)*2
- 计算函数F(x,y,z)=(x+y)/(x-y)+(z+y)/(z-y)的值
- 尽量不要写 if(((X - Y)- Z) > 0 )这样的判断,而要写成 if((X - Y) > Z )
- hdu4282 x^z+y^z+x*y*z=k 解的个数
- 如何编程证明:当n是整数且n>2时,方程x^n+y^n=z^n无正整数解x,y,z
- 概率图模型 conditional independence 一览表
- CATransform3DMakeRotation的x,y,z参数
- x+2*y+5*z = 100
- trimesh2沿x、y、z轴旋转
- 关于glRotatef(angle, x, y, z)函数
- CSU_1511_残缺的棋盘
- 数组非数字键名引号的必要性
- C/C++ 字符串操作1---循环移位
- LeetCode:Length of Last Word
- WINDOWS安装python3.X遇到的错误解决方法
- BN Topic Model 中如何判断conditional independence p(x,y|z)
- PHP CLI模式下的多进程应用
- 启动页面加载
- Java并发教程(Oracle官方资料)
- JAVA_SE系列:06.文档注释和API文档
- OpenStack之日志
- hdu1890 Robotic Sort Splay树,区间反转,lazy标记
- 为什么父类指针可以指向子类反之则不行?
- 使用 NSIS 制作软件安装包