Update app.py

app.py

@@ -108,7 +108,8 @@ if uploaded_file is not None:
                     model.fit(X_train, y_train)
                     y_pred = model.predict(X_test)
                     accuracy = accuracy_score(y_test, y_pred)
-                    results.append([name, accuracy, None])
+                    classification_rep = classification_report(y_test, y_pred)
+                    results.append([name, accuracy, classification_rep])
                 
             else:
                 model_choices = [
@@ -128,7 +129,7 @@ if uploaded_file is not None:
             
             # 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)", "Mean Squared Error" if not 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**")