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Bayesian Networks
book

Bayesian Networks

by Marco Scutari, Jean-Baptiste Denis
June 2014
Intermediate to advanced content levelIntermediate to advanced
241 pages
6h 20m
English
CRC Press
Content preview from Bayesian Networks
B
Probability Distributions
B.1 General Features
A probability distribution is a function that assigns a probability to e ach mea-
surable subset of a set of events. It is associated with a random variable, here
denoted as X.
A discrete probability distribution can assume only a finite or countably
infinite number of values U, such as
{A, B, C, D} or {[0, 5], (5, 7], (8, 10]} or n N, (B.1)
and is characterised by a probability function Pr(·) that satisfies
X
uU
Pr(X = u) = 1 and Pr(X = u) [0, 1] for all u. (B.2)
A continuous probability distribution must assume an infinite number of values
U, typically R or an interval of real numbers, and is characterised ...
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Publisher Resources

ISBN: 9781482225587