V-structure: Difference between revisions
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In graphical models, a '''v-structure''' is a set of three nodes in a graph such that there are two converging arrows and the tails of the arrows are not connected by an arrow.<ref>Judea Pearl. ''Causality''. p. 19.</ref><ref>https://ermongroup.github.io/cs228-notes/representation/directed/</ref> For example, <math>X \rightarrow Z \leftarrow Y</math> is a v-structure. | In graphical models, a '''v-structure''' is a set of three nodes in a graph such that there are two converging arrows and the tails of the arrows are not connected by an arrow.<ref>Judea Pearl. ''Causality''. p. 19.</ref><ref>[https://ermongroup.github.io/cs228-notes/representation/directed/ "Bayesian networks"]. Retrieved September 21, 2018.</ref> For example, <math>X \rightarrow Z \leftarrow Y</math> is a v-structure. | ||
The middle node in a v-structure is called a [[collider]]. (?) | The middle node in a v-structure is called a [[collider]]. (?) | ||
Revision as of 00:32, 22 September 2018
In graphical models, a v-structure is a set of three nodes in a graph such that there are two converging arrows and the tails of the arrows are not connected by an arrow.[1][2] For example, is a v-structure.
The middle node in a v-structure is called a collider. (?)
Some authors seem to distinguish between a v-structure and an immoral v-structure. In this case, "v-structure" seems to only mean that there is a collision, and the "immoral" means the parents are not directly connected.[3]
Terminology
why is this thing called a v-structure? because it looks like a letter V if the two parents are drawn above the common child?
References
- ↑ Judea Pearl. Causality. p. 19.
- ↑ "Bayesian networks". Retrieved September 21, 2018.
- ↑ Su-In Lee. "Bayesian Network Representation". University of Washington CSE 515, Statistical Methods, Spring 2011. p. 14 (slide 27). March 30, 2011. Retrieved September 21, 2018.