From 1c1600a81173bc4400a94596bf45a8a78f788873 Mon Sep 17 00:00:00 2001
From: Andre Anjos <andre.dos.anjos@gmail.com>
Date: Fri, 28 Jun 2024 15:18:05 +0200
Subject: [PATCH] [libs.segmentation.engine.evaluator] Fix doc strings
---
src/mednet/libs/segmentation/engine/evaluator.py | 8 ++++++++
1 file changed, 8 insertions(+)
diff --git a/src/mednet/libs/segmentation/engine/evaluator.py b/src/mednet/libs/segmentation/engine/evaluator.py
index 289071a5..3552aa1d 100644
--- a/src/mednet/libs/segmentation/engine/evaluator.py
+++ b/src/mednet/libs/segmentation/engine/evaluator.py
@@ -532,25 +532,33 @@ def run(
* ``counts``: dictionary where keys are thresholds, and values are
sequence of integers containing the TP, FP, TN, FN (in this order).
+
* ``auc_score``: a float indicating the area under the ROC curve
for the split. It is calculated using a trapezoidal rule.
+
* ``average_precision_score``: a float indicating the area under the
precision-recall curve, calculated using a rectangle rule.
+
* ``curves``: dictionary with 2 keys:
+
* ``roc``: dictionary with 3 keys:
+
* ``fpr``: a list of floats with the false-positive rate
* ``tpr``: a list of floats with the true-positive rate
* ``thresholds``: a list of thresholds uniformily separated by
``steps``, at which both ``fpr`` and ``tpr`` are evaluated.
* ``precision_recall``: a dictionary with 3 keys:
+
* ``precision``: a list of floats with the precision
* ``recall``: a list of floats with the recall
* ``thresholds``: a list of thresholds uniformily separated by
``steps``, at which both ``precision`` and ``recall`` are
evaluated.
+
* ``threshold_a_priori``: boolean indicating if the threshold for unary
metrics where computed with a threshold chosen a priori or a
posteriori in this split.
+
* ``<metric-name>``: a float representing the supported metric at the
threshold that maximizes ``metric``. There will be one entry of this
type for each of the :py:obj:`SUPPORTED_METRIC_TYPE`'s.
--
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