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Fraud_txn_detection_xgboost.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b9371dbb734d44452e09bd4d472340045110a02e4203deb2d6ed1b4b8b0b09ea
+size 119180

app.py

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+import streamlit as st
+import pandas as pd
+import numpy as np
+import joblib
+
+model = joblib.load('Fraud_txn_detection_xgboost.pkl')
+
+st.title('Fraud Transaction detector ')
+st.markdown("Please fill in the detail and press predict")
+
+st.divider()
+
+import streamlit as st
+import numpy as np
+import pandas as pd
+
+st.title("Fraud Detection Input Form")
+
+type_map = {"TRANSFER": 0, "CASH_OUT": 1}
+type_choice = st.selectbox("Transaction Type", options=list(type_map.keys()))
+type_val = type_map[type_choice]
+
+
+amount = st.number_input("Transaction Amount", min_value=0.0, value=1000.0)
+
+oldbalanceOrg = st.number_input("Old Balance (Origin)", min_value=0.0, value=5000.0)
+newbalanceOrig = st.number_input("New Balance (Origin)", min_value=0.0, value=4000.0)
+
+oldbalanceDest = st.number_input("Old Balance (Destination)", min_value=0.0, value=0.0)
+newbalanceDest = st.number_input("New Balance (Destination)", min_value=0.0, value=1000.0)
+
+errordiffbalanceOrg = newbalanceOrig + amount - oldbalanceOrg
+errordiffbalanceDest = oldbalanceDest + amount - newbalanceDest
+
+if st.button("Predict"):
+    input_data = pd.DataFrame([{
+        'type': type_val,
+        'amount': amount,
+        'oldbalanceOrg': oldbalanceOrg,
+        'newbalanceOrig': newbalanceOrig,
+        'oldbalanceDest': oldbalanceDest,
+        'newbalanceDest': newbalanceDest,
+        'errordiffbalanceOrg': errordiffbalanceOrg,
+        'errordiffbalanceDest': errordiffbalanceDest
+    }])
+
+    prediction = model.predict(input_data)[0]
+    st.subheader(f"Prediction : {prediction}")
+
+    if prediction ==1:
+        st.error("This Transaction is fraud")
+    else:
+        st.success("Transaction is not fraud")