| import streamlit as st | |
| import pandas as pd | |
| import numpy as np | |
| import pickle | |
| def main(): | |
| pickle_in = open('RandomForrestClassifier_df1x.pkl', 'rb') | |
| classifier = pickle.load(pickle_in) | |
| columns = ["V1", "V2", "V3", "V4", "V5", "V6", "V7", "V8", "V9", "V10", | |
| "V11", "V12", "V13", "V14", "V15", "V16", "V17", "V18", "V19", "V20", | |
| "V21", "V22", "V23", "V24", "V25", "V26", "V27", "V28", "Amount"] | |
| st.title('Fraud Detector') | |
| for i in columns: | |
| i = st.number_input("Please input the "+i+" value here.") | |
| submit = st.button('Calculate') | |
| input = [[V1, V2, V3, V4, V5, V6, V7, V8, V9, V10, | |
| V11, V12, V13, V14, V15, V16, V17, V18, V19, V20, | |
| V21, V22, V23, V24, V25, V26, V27, V28, Amount]] | |
| input_df = pd.DataFrame(input, columns=columns) | |
| prediction = classifier.predict(input_df) | |
| if prediction == 1: | |
| st.write("The transaction is fraudulant.") | |
| else: | |
| st.write("The transaction is normal.") | |
| main() |