Update app.py

app.py

@@ -13,7 +13,7 @@ def predict_corrected_calcium(total_calcium, total_protein, albumin):
     predicted_value = model.predict([[total_calcium, atr]])[0]
     
     # Return the result string
-    return f"{predicted_value:.2f}. The model is a RDF Regression Model with a MSE of 0.06 and R-squared of 0.931."
+    return f"{predicted_value:.2f}.\n\nThe model has a MSE of 0.06, MAD of 0.08 and R-squared of 0.931."
 
 # Define the Gradio interface
 interface = gr.Interface(fn=predict_corrected_calcium, 
@@ -21,6 +21,6 @@ interface = gr.Interface(fn=predict_corrected_calcium,
                                  gr.inputs.Number(label="Total Protein"),
                                  gr.inputs.Number(label="Albumin")],
                          outputs=gr.outputs.Textbox(label="Corrected Calcium in mg/dL"),
-                         title="RandomForestRegressor assisted Calcium Correction (RaCC)")
+                         title="XGBoost assisted Calcium Correction (RaCC)")
 
 interface.launch()