@@ -32,7 +32,7 @@ def __init__(
3232 self ._category_score (
3333 truth_probabilities [category ],
3434 prediction_probabilities [category ],
35- truth_weights ,
35+ truth_weights . score_weight ,
3636 category ,
3737 )
3838 for category in categories
@@ -69,7 +69,7 @@ def __init__(
6969 def _category_score (
7070 truth_category_probabilities : pd .Series ,
7171 prediction_category_probabilities : pd .Series ,
72- truth_weights : pd .DataFrame ,
72+ truth_score_weights : pd .Series ,
7373 category : str ,
7474 ) -> pd .Series :
7575 truth_binary_values : pd .Series = truth_category_probabilities .gt (0.5 )
@@ -78,7 +78,7 @@ def _category_score(
7878 category_cm = create_binary_confusion_matrix (
7979 truth_binary_values = truth_binary_values .to_numpy (),
8080 prediction_binary_values = prediction_binary_values .to_numpy (),
81- weights = truth_weights . score_weight .to_numpy (),
81+ weights = truth_score_weights .to_numpy (),
8282 name = category ,
8383 )
8484
@@ -93,18 +93,18 @@ def _category_score(
9393 'auc' : metrics .auc (
9494 truth_category_probabilities ,
9595 prediction_category_probabilities ,
96- truth_weights . score_weight ,
96+ truth_score_weights ,
9797 ),
9898 'auc_sens_80' : metrics .auc_above_sensitivity (
9999 truth_category_probabilities ,
100100 prediction_category_probabilities ,
101- truth_weights . score_weight ,
101+ truth_score_weights ,
102102 0.80 ,
103103 ),
104104 'ap' : metrics .average_precision (
105105 truth_category_probabilities ,
106106 prediction_category_probabilities ,
107- truth_weights . score_weight ,
107+ truth_score_weights ,
108108 ),
109109 },
110110 index = [
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