# Conflict

Conflict is a measure that detects evidence that is conflicting or rare. The greater the conflict value above zero, the more likely the evidence is in conflict, or rare.

**Conflict = log((P(e1)P(e2)...P(ei)) / P(e))**,
where P(e1), P(e2) etc... are the likelihoods of each variable
considered in isolation, and P(**e**) is the likelihood of the all the evidence together (see Log likelihood ).

If evidence on a variable X agrees with evidence on another variable Y, then often `P(X=x)P(Y=y) < P(X=x, Y=y)`

, and will therefore lead to a negative conflict.

Bayes Server supports conflict on networks with discrete and/or continuous variables, and also dynamic Bayesian networks. However while calculations involving discrete variables are fast, there is additional overhead for continuous variables.