Update app.py

app.py

@@ -65,13 +65,13 @@ with tab1:
         - **AUC** (Area Under the Curve) measures how well the model separates the classes.  
         - AUC ranges from 0 to 1. Closer to 1 = better.
         """)
-st.image(
-    "https://upload.wikimedia.org/wikipedia/commons/6/6b/Roccurves.png",
-    caption="ROC Curves Example",
-    width=400  # 👈 adjust as needed (300–600 works well)
-)
+    st.image(
+        "https://upload.wikimedia.org/wikipedia/commons/6/6b/Roccurves.png",
+        caption="ROC Curves Example",
+        width=400  # 👈 adjust as needed (300–600 works well)
+    )
 
-        st.info("✔️ Best for evaluating probabilistic classifiers.")
+    st.info("✔️ Best for evaluating probabilistic classifiers.")
 
     st.markdown("---")
     st.success("📌 Tip: Use **F1 Score** or **ROC-AUC** in imbalanced classification problems!")