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| import streamlit as st | |
| import pickle | |
| import pandas as pd | |
| st.title("BEHAIVER PREDICTION") | |
| # Load the trained model | |
| with open('logistic_regression_model.pkl', 'rb') as f: | |
| model = pickle.load(f) | |
| # Create input fields | |
| age = st.number_input("Enter age:", min_value=0) | |
| sex = st.radio("Select sex:", ("FEMALE", "MALE")) | |
| present_city = st.radio("Select present city:", ("Bengaluru City", "Other")) | |
| present_state = st.radio("Select present state:", ("Karnataka", "Other")) | |
| # Convert inputs to model format | |
| sex_female = 1 if sex == 'FEMALE' else 0 | |
| sex_male = 1 if sex == 'MALE' else 0 | |
| city_bengaluru = 1 if present_city == 'Bengaluru City' else 0 | |
| state_karnataka = 1 if present_state == 'Karnataka' else 0 | |
| # Create a data frame for the input data | |
| input_data = pd.DataFrame({ | |
| 'age': [age], | |
| 'Sex_FEMALE': [sex_female], | |
| 'Sex_MALE': [sex_male], | |
| 'PresentCity_Bengaluru City': [city_bengaluru], | |
| 'PresentState_Karnataka': [state_karnataka] | |
| }) | |
| # Make a prediction | |
| if st.button("Predict Behavioral Status"): | |
| prediction = model.predict(input_data) | |
| st.write(f"The predicted Behavioral Status is: {prediction[0]}") | |