|
|
|
|
|
|
|
|
import streamlit as st
|
|
|
import numpy as np
|
|
|
import joblib
|
|
|
|
|
|
|
|
|
kmeans = joblib.load("kmeans_model.pkl")
|
|
|
scaler = joblib.load("scaler.pkl")
|
|
|
|
|
|
st.title("🛍️ Online Retail Müşteri Segmentasyonu")
|
|
|
|
|
|
st.markdown("Müşterinin Recency, Frequency, Monetary bilgilerini girin:")
|
|
|
|
|
|
|
|
|
recency = st.number_input("Recency (Son alışveriş gün farkı)", min_value=0)
|
|
|
frequency = st.number_input("Frequency (Sipariş sayısı)", min_value=0)
|
|
|
monetary = st.number_input("Monetary (Toplam harcama)", min_value=0)
|
|
|
|
|
|
if st.button("Segmenti Tahmin Et"):
|
|
|
input_data = np.array([[recency, frequency, monetary]])
|
|
|
input_scaled = scaler.transform(input_data)
|
|
|
cluster = kmeans.predict(input_scaled)[0]
|
|
|
st.success(f"🧠 Bu müşteri Segment {cluster} grubuna aittir.")
|
|
|
|
