Update cancer.py

cancer.py

@@ -105,10 +105,20 @@ if st.button("Predict Cancer Presence"):
     if 'trained_model' in st.session_state:
         model = st.session_state['trained_model']
         x_train = st.session_state['x_train']
+
+        # Create DataFrame for input
         input_df = pd.DataFrame(input_data, columns=x_train.columns)
+
+        # Convert numeric inputs explicitly to float
+        for col in ['Age', 'Tumor_Size']:
+            input_df[col] = pd.to_numeric(input_df[col], errors='coerce')
+
+        # Apply preprocessing
         input_transformed = model.named_steps['preprocessor'].transform(input_df)
+
+        # Make prediction
         prediction = model.named_steps['classifier'].predict(input_transformed)
-        
+
         if prediction[0] == 1:
             st.markdown("<h3 style='color: red;'>Cancer Prediction: Positive 🟥</h3>", unsafe_allow_html=True)
             st.write("Unfortunately, the model predicts the presence of cancer. Please consult a doctor for further advice.")