📕 subnode [[@KGBicheno/log odds]]
in 📚 node [[log-odds]]
📓
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
- public document at doc.anagora.org/log-odds
- video call at meet.jit.si/log-odds