@@ -49,15 +49,15 @@ def measurement(y_true, y_pred, eval_metrics, num_tabs=1):
4949 results = {}
5050 for eval_metric in eval_metrics :
5151 if eval_metric == "Accuracy" :
52- results [eval_metric ] = round (accuracy_score (y_true , y_pred ) , 2 )
52+ results [eval_metric ] = round (accuracy_score (y_true , y_pred ), 4 )
5353 elif eval_metric == "Precision" :
54- results [eval_metric ] = round (precision_score (y_true , y_pred , average = "macro" ) , 4 )
54+ results [eval_metric ] = round (precision_score (y_true , y_pred , average = "macro" ), 4 )
5555 elif eval_metric == "Recall" :
56- results [eval_metric ] = round (recall_score (y_true , y_pred , average = "macro" ) , 4 )
56+ results [eval_metric ] = round (recall_score (y_true , y_pred , average = "macro" ), 4 )
5757 elif eval_metric == "F1-score" :
58- results [eval_metric ] = round (f1_score (y_true , y_pred , average = "macro" ) , 4 )
58+ results [eval_metric ] = round (f1_score (y_true , y_pred , average = "macro" ), 4 )
5959 elif eval_metric == "P@min" :
60- results [eval_metric ] = round (np .min (precision_score (y_true , y_pred , average = None )) , 4 )
60+ results [eval_metric ] = round (np .min (precision_score (y_true , y_pred , average = None )), 4 )
6161 elif eval_metric == "r-Precision" :
6262 results [eval_metric ] = round (cal_r_precision (y_true , y_pred ), 4 )
6363 elif eval_metric == "AUC" :
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