Update app.py

app.py

@@ -8,7 +8,7 @@ df_metrics = df.pivot_table(index='dataset', columns='model', values=['accuracy'
 
 # Reorganize columns
 cols_order = []
-metrics = ['accuracy', 'precision', 'recall', 'F1_score']
+metrics = ['accuracy', 'precision', 'recall', 'f1_score']
 models = ['DecisionTree', 'RandomForest', 'SVM', 'KNN', 'LogisticRegression']
 
 for metric in metrics:
@@ -19,11 +19,16 @@ df_metrics = df_metrics[cols_order]
 
 # Rename columns for better readability
 new_cols = []
-for col in df_metrics.columns:
-    metric, model = col
-    new_cols.append(f'{model.replace("DecisionTree", "DT").replace("RandomForest", "RF").replace("LogisticRegression", "LR")} {metric.capitalize()}')
+for metric, model in df_metrics.columns:
+    model_short = model.replace("DecisionTree", "DT") \
+                       .replace("RandomForest", "RF") \
+                       .replace("LogisticRegression", "LR")
+
+    metric_name = "F1 Score" if metric == "f1_score" else metric.capitalize()
+    new_cols.append(f"{model_short} {metric_name}")
 
 df_metrics.columns = new_cols
+
 df_metrics = df_metrics.sort_index(key=lambda x: x.str[1:].astype(int))
 df_compare = pd.read_csv("pairwise_comparison_results.csv")