📕 subnode [[@KGBicheno/accuracy]]
in 📚 node [[accuracy]]
📓
garden/KGBicheno/Artificial Intelligence/Introduction to AI/Week 3 - Introduction/Definitions/Accuracy.md by @KGBicheno
accuracy
Go back to the [[AI Glossary]]
The fraction of predictions that a classification model got right. In multi-class classification, accuracy is defined as follows: $$Accuracy = \frac{Correct Predictions}{Total Number of Examples} $$
In binary classification, accuracy has the following definition:
$$Accuracy = \frac{True Positives + True Negatives}{Total Number of Examples} $$
See true positive and true negative.
📖 stoas
- public document at doc.anagora.org/accuracy
- video call at meet.jit.si/accuracy