The notion of a

conditional probability (X is probable to degree x on condition y), applies to those judgments that are more or less objective as well as those that are obviously subjective.

In other words, we transform the maximization of the

conditional probability P([P.sub.t]|[P.sub.t-1]...

It is an action, it makes the weight of reasons to take means insensitive to better means and it does not necessarily count actions with any positive

conditional probability as means.

In this study, a

conditional probability distribution was applied for meteorological drought analysis based on copulas.

(ii) P = {p([x.sub.i] | pa([x.sub.i])), [x.sub.i] [member of] X} denotes the

conditional probability table (CPT) of all the nodes in B, and: pa([x.sub.i]) = {[x.sub.p], [x.sub.p] [right arrow] [x.sub.i] [conjunction] ([x.sub.p] [right arrow] [x.sub.i]) [member of] E [conjunction] [x.sub.p] [member of] X [conjunction] [x.sub.i] [member of] X}, pa([x.sub.i]), denotes the parent node set of [x.sub.i].

Conditional Probability of Overtopping due to Flooding

A small computer program could be installed in the mobile health unit or ambulance according to the

conditional probability of the related parameters, and the suspected stroke subtype may be easily determined.

To address my first two research questions and estimate the

conditional probability of high school graduation in a given year after high school entry (what 1 refer to here as the graduation probability profile) among students with disabilities, I had to ensure that students in my sample had a clear entry-to-high school starting point that then became the "origin" of their high school careers.

The strength of a link between two nodes was expressed as a 'probabilistic dependency', which was quantified by a

conditional probability table (CPT).

Constructing a BN classifier requires learning a network structure with set of

Conditional Probability Tables (CPTs) [6].

For discrete random variables, this

conditional probability is often represented by a table, listing the local probability that a child node takes on each of the feasible values--for each combination of values of its parents.

Bell assumes that a

conditional probability P(X | Y) represents a physical causal influence of Y on X.