Update README.md

README.md

@@ -121,12 +121,6 @@ div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
 
 ## Evaluation Results
 
-plt.figure(figsize=(15,20))
-
-tree.plot_tree(dt, rounded =True, class_names = ['0','1'],
-      proportion=True, filled =True, impurity=False,fontsize=10);
-
-
               precision    recall  f1-score   support
 
            0       1.00      0.74      0.85     20189
@@ -140,6 +134,13 @@ The overall accuracy of the model was 89%. For Class 0, the precision score was
 
 The model could possibly be used for real scenarios, but not for high risk use. It would be helpful in situations where you only need a general screening of phishing vs legitimate websites. So although it is accurate, it is not accurate enough. However, I would still trust this model. It performs well and behaves predictably. If more precision/recall is needed, then it would certainly make sense to use a more complex model. It all depends on what the model is being used for.
 
+## Visualization
+
+plt.figure(figsize=(15,20))
+
+tree.plot_tree(dt, rounded =True, class_names = ['0','1'],
+      proportion=True, filled =True, impurity=False,fontsize=10);
+
 # Model Card Authors
 
 Anthony Martinez