Bump for a bad thread, because I need to learn bayesian networks during the following 2 weeks
Name:
Anonymous2014-03-24 4:42
go on coursera or something
Name:
Anonymous2014-03-24 5:36
READ A GODDAMN BOOK
Name:
Anonymous2014-03-24 7:41
>2014
>reading books
top lel
Now give me a youtube tutorial, cunt.
Name:
Anonymous2014-03-24 9:28
Suppose that there are two events which could cause grass to be wet: either the sprinkler is on or it's raining. Also, suppose that the rain has a direct effect on the use of the sprinkler (namely that when it rains, the sprinkler is usually not turned on). Then the situation can be modeled with a Bayesian network (shown). All three variables have two possible values, T (for true) and F (for false).
"The bulk of human knowledge is organized around causal, not probabilistic relationships, and the grammar of probability calculus is insufficient for capturing those relationships. Specifically, the building blocks of our scientific and everyday knowledge are elementary facts such as “mud does not cause rain” and “symptoms do not cause disease” and those facts, strangely enough, cannot be expressed in the vocabulary of probability calculus."