Harmonizing dependency and independence

Former Welfare Families Independence and Recurring Dependency

care, an organlzntlon must have st least half of Its enrolled membership composed of persons under age 65 and must have an open-enrollment perxod durmg uh~ch It R 111 accept Medlcnre beneficnmes to the lnmts of Its cnpaclty m the order ,n \\hlch they apply (\%lth prowaons for RBIYB~‘S and exceptlox) The HMO premmm rate or otha charge to MedIcare enrollees need not be commumty-rated but can be b...

Girth, minimum degree, independence, and broadcast independence

An independent broadcast on a connected graph $G$is a function $f:V(G)to mathbb{N}_0$such that, for every vertex $x$ of $G$, the value $f(x)$ is at most the eccentricity of $x$ in $G$,and $f(x)>0$ implies that $f(y)=0$ for every vertex $y$ of $G$ within distance at most $f(x)$ from $x$.The broadcast independence number $alpha_b(G)$ of $G$is the largest weight $sumlimits_{xin V(G)}f(x)$of an ind...

The Implication of Probabilistic Conditional Independence and Embedded Multivalued Dependency

It has been suggested that Bayesian networks and relational databases are different because the implication problems for probabilistic conditional independence and embedded multivalued dependency do not always coincide. The present study indicates that the implication problems coincide on solvable classes of dependencies and differ on unsolvable classes. We therefore maintain that Bayesian netw...

Dependency networks based classifiers: learning models by using independence

In this paper we propose using dependency networks (Heckerman et al., 2000), that is a probabilistic graphical model similar to Bayesian networks, to model classifiers. The main difference between these two models is that in dependency networks cycles are allowed, and this fact has the consequence that the automatic learning process is much easier and can be parallelized. These properties make ...

Harmonizing for health.