📚 node [[log odds|log odds]]
Welcome! Nobody has contributed anything to 'log odds|log odds' yet. You can:
  • Write something in the document below!
    • There is at least one public document in every node in the Agora. Whatever you write in it will be integrated and made available for the next visitor to read and edit.
  • Write to the Agora from social media.
    • If you follow Agora bot on a supported platform and include the wikilink [[log odds|log odds]] in a post, the Agora will link it here and optionally integrate your writing.
  • Sign up as a full Agora user.
    • As a full user you will be able to contribute your personal notes and resources directly to this knowledge commons. Some setup required :)
⥅ related node [[log odds]]
⥅ node [[log-odds]] pulled by Agora
📓 garden/KGBicheno/Artificial Intelligence/Introduction to AI/Week 3 - Introduction/Definitions/Log-Odds.md by @KGBicheno

log-odds

Go back to the [[AI Glossary]]

The logarithm of the odds of some event.

If the event refers to a binary probability, then odds refers to the ratio of the probability of success (p) to the probability of failure (1-p). For example, suppose that a given event has a 90% probability of success and a 10% probability of failure. In this case, odds is calculated as follows:

$$ odds=\frac{p}{(1-p)}=\frac{(.9)}{(.1)}=9 $$

The log-odds is simply the logarithm of the odds. By convention, "logarithm" refers to natural logarithm, but logarithm could actually be any base greater than 1. Sticking to convention, the log-odds of our example is therefore:

$$ log-odds = ln(9) = 2.2 $$

The log-odds are the inverse of the sigmoid function.
📖 stoas
⥱ context
← back
ai glossary

↑ pushing here
(none)

↓ pulling this
(none)
→ forward
(none)
🔎 full text search for 'log odds|log odds'