Update app.py

app.py

@@ -114,9 +114,13 @@ if uploaded_file is not None:
                 for name, model in model_choices:
                     model.fit(X_train, y_train)
                     y_pred = model.predict(X_test)
+                    
+                    # Accuracy and Classification Report
                     accuracy = accuracy_score(y_test, y_pred)
-                    class_report = classification_report(y_test, y_pred)
-                    results.append([name, accuracy, class_report])
+                    classification_report_output = classification_report(y_test, y_pred)
+                    
+                    # Append results
+                    results.append([name, accuracy, classification_report_output])
                 
             else:  # Regression models
                 model_choices = [
@@ -131,12 +135,17 @@ if uploaded_file is not None:
                 for name, model in model_choices:
                     model.fit(X_train, y_train)
                     y_pred = model.predict(X_test)
+                    
+                    # Mean Squared Error (MSE) for regression tasks
                     mse = mean_squared_error(y_test, y_pred)
+                    
+                    # Append results
                     results.append([name, None, mse])
             
             # Display results in a table
             st.subheader("Model Performance Results")
-            results_df = pd.DataFrame(results, columns=["Model", "Accuracy" if is_classification else "Accuracy (N/A)", "Classification Report" if is_classification else "MSE (N/A)"])
+            results_df = pd.DataFrame(results, columns=["Model", "Accuracy" if is_classification else "Accuracy (N/A)", 
+                                                        "Classification Report" if is_classification else "MSE (N/A)"])
             
             # Bold the headers
             st.markdown(f"**Model Performance Results**")