Skip to content
Open
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions representation/directed/index.md
Original file line number Diff line number Diff line change
Expand Up @@ -16,9 +16,9 @@ The kinds of models that we will see here are referred to as *Bayesian networks*

## Probabilistic modeling with Bayesian networks

Directed graphical models (a.k.a. Bayesian networks) are a family of probability distributions that admit a compact parametrization that can be naturally described using a directed graph.
Directed graphical models (a.k.a. Bayesian networks) are a family of probability distributions that admit a compact parameterization that can be naturally described using a directed graph.

The general idea behind this parametrization is surprisingly simple.
The general idea behind this parameterization is surprisingly simple.

Recall that by the chain rule, we can write any probability $$p$$ as:

Expand Down