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| import streamlit as st | |
| from joblib import load | |
| model = load("kmeans_model.pkl") | |
| st.title("Customer Segmentation") | |
| # inputs | |
| Sex = st.selectbox("gender of a customer",options= ["Male","Female"]) | |
| Sex=1 if Sex=="Male" else 0 | |
| Marital_status = st.selectbox("Marital Status",options= ["Single","Non-single"]) | |
| Marital_status=0 if Sex=="Single" else 1 | |
| Age = st.number_input("age of the customer",min_value=18,max_value=90) | |
| Education = st.selectbox("Education Level of education of the customer", | |
| options= ["other / unknown","high school","university","graduate school"]) | |
| Education_d={"other / unknown":0,"high school":1,"university":2,"graduate school":3} | |
| Education = Education_d[Education] | |
| Income = st.number_input("Self-reported annual income in US dollars of the customer",step=100,min_value=30000) | |
| Occupation = st.selectbox("occupation of the customer", | |
| options= ["unemployed / unskilled","skilled employee","highly qualified employee"]) | |
| Occupation_d={"unemployed / unskilled":0,"skilled employee":1,"highly qualified employee":2} | |
| Occupation = Occupation_d[Occupation] | |
| Settlement_size = st.selectbox("The size of the city that the customer lives in", | |
| options= ["small city","mid-sized city","big city"]) | |
| Settlement_size_d={"small city":0,"mid-sized city":1,"big city":2} | |
| Settlement_size = Settlement_size_d[Settlement_size] | |
| values = [Sex,Marital_status, Age,Education,Income,Occupation,Settlement_size] | |
| if st.button("Predict"): | |
| label = model.predict([values])[0] | |
| st.success(f"Customer Belongs to Segment *{label}*") |