| import streamlit as st | |
| import pandas as pd | |
| from sklearn.preprocessing import StandardScaler | |
| def predict_cluster(model, selected_features): | |
| st.write("### Predict Cluster") | |
| user_input = {} | |
| for feature in selected_features: | |
| user_input[feature] = st.number_input(f'Enter {feature}', value=0.0) | |
| user_df = pd.DataFrame(user_input, index=[0]) | |
| scaler = StandardScaler() | |
| user_df_scaled = scaler.fit_transform(user_df) | |
| cluster = model.predict(user_df_scaled) | |
| st.write(f'The predicted cluster for the input data is: {cluster[0]}') | |