fraud_detection.py

import streamlit as st
import pandas as pd
import joblib

model= joblib.load(r"d:\dell_backup_25\d-drive\Masai_Ds\Python\fraud_detection_pipeline_model.pkl")
st.title("Fraud Detection Prediction App")
st.markdown("Please enter the transaction details and use the predict button")

st.divider()

transaction_type = st.selectbox("Transaction Type", ["PAYMENT", "TRANSFER", "CASH_OUT"])
amount = st.number_input("Amount", min_value=0.0, value=1000.0)
oldbalanceOrg=st.number_input("Old Balance (Sender)", min_value=0.0, value=10000.0)
newbalanceOrig=st.number_input("New Balance (Sender)", min_value=0.0, value=9000.0)
oldbalanceDest=st.number_input("Old Balance (Receiver)", min_value=0.0, value=0.0)
newbalanceDest=st.number_input("New Balance (Receiver)", min_value=0.0, value=0.0)

if st.button("Predict"):
    input_data = pd.DataFrame([{
        
        "type": transaction_type,
        "amount": amount,
        "oldbalanceOrg": oldbalanceOrg,
        "newbalanceOrig": newbalanceOrig,
        "oldbalanceDest": oldbalanceDest,
        "newbalanceDest": newbalanceDest
    }])
    
    prediction = model.predict(input_data)[0]

    st.subheader(f"Prediction : '{int(prediction)}'")
    
    if prediction == 1:
        st.error("The transaction can be fraud")
    else:
        st.success("This transaction looks like it is not a fraud.")