From c24aa0d4967029f204f92e713d07cdeab59b755d Mon Sep 17 00:00:00 2001 From: Jelle Teijema Date: Thu, 31 Oct 2024 15:07:10 +0100 Subject: [PATCH] Update figure URL after upload in README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index e8032eb..6611071 100644 --- a/README.md +++ b/README.md @@ -168,7 +168,7 @@ $$\text{Normalized Loss} = \frac{Ny \times \left(Nx - \frac{Ny - 1}{2}\right) - The lower the loss, the closer the model is to the perfect recall curve, indicating higher performance. -![Recall plot illustrating loss metric](https://github.com/jteijema/asreview-insights/blob/loss-metric/figures/loss_metric_example.png?raw=true) +![Recall plot illustrating loss metric](https://github.com/asreview/asreview-insights/blob/main/figures/loss_metric_example.png?raw=true) In this figure, the green area between the recall curve and the perfect recall line is the lossed performance, which is then normalized for the total area (green and red combined).