How did we get this table in bayesian belief network?

[shivajikobardan]

How did we get these values?

https://courses.engr.illinois.edu/ece448/sp2020/slides/lec15.pdf
This is the slide that I am referring to.

I honestly don’t understand what is going on here. Please guide me a bit here.

 

[blamocur]

Here is my understanding of the slide:

1. The point is to figure out [imath]P(B|M)[/imath], which is equal to [imath]\frac{B\cap M}{P(M)}[/imath].
2. We know [imath]P(M) = P(M|A) + P(M|\neg A) = 0.71[/imath], but we don't know [imath]P(B\cap M)[/imath].
3. In order to compute [imath]P(B\cap M)[/imath] we collect all the relevant probabilities in one table. There are 4 relevant events out of 5: [imath]B,E,A,M[/imath], and the table represents all 16 combinations of [imath]X[/imath] and [imath]\neg X[/imath], where [imath]X[/imath] is one of [imath]B,E,A,M[/imath].

Does this make sense?

 

[shivajikobardan]

Here is my understanding of the slide:

1. The point is to figure out [imath]P(B|M)[/imath], which is equal to [imath]\frac{B\cap M}{P(M)}[/imath].
2. We know [imath]P(M) = P(M|A) + P(M|\neg A) = 0.71[/imath], but we don't know [imath]P(B\cap M)[/imath].
3. In order to compute [imath]P(B\cap M)[/imath] we collect all the relevant probabilities in one table. There are 4 relevant events out of 5: [imath]B,E,A,M[/imath], and the table represents all 16 combinations of [imath]X[/imath] and [imath]\neg X[/imath], where [imath]X[/imath] is one of [imath]B,E,A,M[/imath].

Does this make sense?

hmm no ..honestly this is easily the toughest stuffs i have came across. it feels like my brain has become softer after spending 10+ hrs in this.

 

[blamocur]

hmm no ..honestly this is easily the toughest stuffs i have came across. it feels like my brain has become softer after spending 10+ hrs in this.

It took me some time too to get a sense of what's going on in those slides.