Update pages/4_Model_Creation_and_Evaluation.py

pages/4_Model_Creation_and_Evaluation.py

@@ -221,9 +221,9 @@ if df is not None:
     y_pred = model.predict(x_test_std)
     
     # Evaluation metrics
-    st.write(print("Accuracy:", accuracy_score(y_test, y_pred)))
-    st.write(print("Classification Report:\n", classification_report(y_test, y_pred)))
-    st.write(print("Confusion Matrix:\n", confusion_matrix(y_test, y_pred)))
+    st.write("Accuracy:", accuracy_score(y_test, y_pred))
+    st.write(Classification Report:\n", classification_report(y_test, y_pred))
+    st.write("Confusion Matrix:\n", confusion_matrix(y_test, y_pred))
 
     import streamlit as st
     import pandas as pd