v.0.1

app.py

@@ -25,23 +25,23 @@ numerical_inputs = {}
 categorical_inputs = {}
 
 try:
-    numerical_features = list(scaler.feature_names_in_) 
+    numerical_features = list(scaler.feature_names_in_)
     categorical_features = list(label_encoders.keys())
 except AttributeError:
     st.error("Scaler or encoders are not properly loaded.")
     st.stop()
 
+# ✅ FIXED: Ensure numerical inputs always have valid default values
 for feature in numerical_features:
-    numerical_inputs[feature] = st.number_input(f"Enter {feature}", value=0.0)
+    numerical_inputs[feature] = st.number_input(f"Enter {feature}", value=0.0, step=0.1, format="%.2f")
 
 for feature in categorical_features:
-    if label_encoders[feature].classes_.size > 0:  
+    if label_encoders[feature].classes_.size > 0:
         categorical_inputs[feature] = st.selectbox(f"Select {feature}", label_encoders[feature].classes_)
     else:
         st.error(f"Label encoder for {feature} is empty.")
         st.stop()
 
-
 if st.button("Predict"):
     try:
         for feature in categorical_inputs:
@@ -58,3 +58,4 @@ if st.button("Predict"):
 
     except Exception as e:
         st.error(f"Prediction error: {e}")
+