use `binary` average in all metrics

leaderboard.py

@@ -91,7 +91,7 @@ def get_algorithm_scores_v2(df):
       sel_df = df[mask]
     
       samples_tested.append(len(sel_df))
-      tpr_scores.append(round(recall_score(sel_df.gnd_truth.values, sel_df.pred.values, pos_label=1), 3))
+      tpr_scores.append(round(recall_score(sel_df.gnd_truth.values, sel_df.pred.values, pos_label=1, average="binary"), 3))
     
     
     for c in columns2:
@@ -99,21 +99,21 @@ def get_algorithm_scores_v2(df):
       sel_df = df[mask]
     
       samples_tested.append(len(sel_df))
-      tpr_scores.append(round(recall_score(sel_df.gnd_truth.values, sel_df.pred.values, pos_label=1), 3))
+      tpr_scores.append(round(recall_score(sel_df.gnd_truth.values, sel_df.pred.values, pos_label=1, average="binary"), 3))
     
     mask = (df.label != "real")
     sel_df = df[mask]
 
-    tpr_scores.append(round(recall_score(sel_df.gnd_truth.values, sel_df.pred.values, pos_label=1), 3))
+    tpr_scores.append(round(recall_score(sel_df.gnd_truth.values, sel_df.pred.values, pos_label=1, average="binary"), 3))
 
     mask = (df.label == "real")
     sel_df = df[mask]
 
-    tnr_scores.append(round(recall_score(sel_df.gnd_truth.values, sel_df.pred.values, pos_label=0), 3))
+    tnr_scores.append(round(recall_score(sel_df.gnd_truth.values, sel_df.pred.values, pos_label=0, average="binary"), 3))
 
     sel_df = df.copy()
     samples_tested.append(len(sel_df))
-    f1_scores.append(round(f1_score(sel_df.gnd_truth.values, sel_df.pred.values, average="macro"), 3))
+    f1_scores.append(round(f1_score(sel_df.gnd_truth.values, sel_df.pred.values, average="binary"), 3))
 
         
     lb = pd.DataFrame({"Sample": columns + columns2 + ["overall"], "Num Samples": samples_tested,