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→Causal structures
[[Feedforward neural network]]s are another example.
[[Feedforward neural network]]s are another example.
=== Causal structures ===
=== Causal structures 因果结构 ===
{{main|Bayesian network}}
{{main|Bayesian network}}
The converse is also true. That is in any application represented by a directed acyclic graph there is a causal structure, either an explicit order or time in the example or an order which can be derived from graph structure. This follows because all directed acyclic graphs have a [[#Topological ordering|topological ordering]], i.e. there is at least one way to put the vertices in an order such that all edges point in the same direction along that order.
The converse is also true. That is in any application represented by a directed acyclic graph there is a causal structure, either an explicit order or time in the example or an order which can be derived from graph structure. This follows because all directed acyclic graphs have a [[#Topological ordering|topological ordering]], i.e. there is at least one way to put the vertices in an order such that all edges point in the same direction along that order.
反之亦然。也就是说，在由有向无环图表示的任何应用程序中，都有一个因果结构，或者是示例中的显式顺序或时间，或者是可以从图结构派生的顺序。这是因为所有有向无环图都具有拓扑排序，即至少有一种方法可以将顶点按顺序排列，使所有边沿着该顺序指向同一方向。
de:Graph (Graphentheorie)#Teilgraphen.2C Wege und Zyklen
de:Graph (Graphentheorie)#Teilgraphen.2C Wege und Zyklen