Delete src

src/Fraud_txn_detection_xgboost.pkl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:b9371dbb734d44452e09bd4d472340045110a02e4203deb2d6ed1b4b8b0b09ea
-size 119180

src/streamlit_app.py

@@ -1,53 +0,0 @@
-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")