Update app.py

app.py

@@ -241,7 +241,7 @@ def visualize_ROC(set_threshold,set_input):
   x = np.linspace(0, 1, 500)
 
   plt.plot(thres_list, f1_score_list, label = 'F1-score', c='black', linestyle='-')
-  plt.plot(thres_list, g_mean_list, label = 'G-mean', c='black', linestyle='-')
+  plt.plot(thres_list, g_mean_list, label = 'G-mean', c='red', linestyle='-')
 
   plt.xlim(0, 1)
   plt.ylim(0, 1)
@@ -259,8 +259,9 @@ def visualize_ROC(set_threshold,set_input):
   ax.spines['bottom'].set_color('black')
   ax.spines['top'].set_color('black')
   ax.spines['right'].set_color('black')
-  plt.xlabel('False Positive Rate (1 - specificity)')
-  plt.ylabel('True Positive Rate (Recall)')
+  plt.xlabel('Threshold cut-off')
+  plt.ylabel('F1-score & G-mean')
+  plt.legend()
   plt.text(set_threshold, f1_score_cur, 'F1-score:%s, G-mean:%s' % (round(f1_score_cur,2),round(g_mean_cur,2)))
   plt.title("Threshold tuning curves (F1-score & G-mean)", fontsize=20)
   plt.tight_layout()