omar94khan/ML

1import streamlit as st2import pandas as pd3import numpy as np4import pickle5from sklearn.preprocessing import MinMaxScaler6 7def main():8    st.title('Fraud Detector')9 10    file = st.file_uploader("Choose a file")11 12    if file is not None:13        classifier = pickle.load(open('RandomForrestClassifier_df4x.pkl', 'rb'))14        15        df = pd.read_csv(file)16        st.write("The dataset you uploaded is:")17        st.write(df)18        19        for col in ['Class']:20            df = df.loc[:,df.columns != col]21        df = pd.DataFrame(MinMaxScaler().fit(df).transform(df), columns=df.columns)22 23 24        result_df = pd.DataFrame(classifier.predict_proba(df))[1]25            26        st.write("Output DataFrame depicting probability of the transaction being fraudulant.")27        st.write(result_df)28    29main()