Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Add definition for 'ROC curve' (English) #594

Merged
merged 5 commits into from
Oct 16, 2023
Merged

Add definition for 'ROC curve' (English) #594

Changes from all commits
Commits
Show all changes
5 commits
Select commit Hold shift + click to select a range
268ec56
Update glossary.yml
abhicc Aug 31, 2023
ed27842
Update glossary.yml
elletjies Oct 12, 2023
3968f2a
Merge branch 'main' into abhicc_ROC
jsteyn Oct 16, 2023
5e1b320
Update glossary.yml
jsteyn Oct 16, 2023
fc56fbf
Update glossary.yml
jsteyn Oct 16, 2023
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
12 changes: 12 additions & 0 deletions glossary.yml
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -10221,3 +10221,15 @@
A hidden layer in a [neural network](#neural_network) refers to the layers of neurons that are
not directly connected to input or output. The layers are "hidden" because you do not directly
observe their input and output values.

- slug: roc_curve
ref:
- machine_learning
- classification
en:
term: "ROC Curve"
def: >
A ROC curve (Receiver Operating Characteristic curve) is a graph that displays the performance
of a binary classifier at different [classification](#classification) thresholds. The curve is
obtained by plotting the True Positive Rate (also known as Recall or [Sensitivity](#sensitivity))
along the vertical axis and the False Positive Rate along the horizontal axis.