App.py

app.py

@@ -0,0 +1,27 @@
+   
+import streamlit as st
+import pandas as pd
+import numpy as np
+import pickle
+
+def main():
+    st.title('Fraud Detector')
+
+    file = st.file_uploader("Choose a file")
+
+    if file is not None:
+        classifier = pickle.load(open('RandomForrestClassifier_df4x.pkl', 'rb'))
+        
+        df = pd.read_csv(file)
+        for col in ['Class']:
+            df = df.loc[:,df.columns != col]
+        df = pd.DataFrame(MinMaxScaler().fit(df).transform(df), columns=df.columns)
+        st.write("The dataset you uploaded is:")
+        st.write(df)
+
+        result_df = pd.DataFrame(classifier.predict_proba(df))
+            
+        st.write("Output DataFrame depicting probability of the transaction being fraudulant.")
+        st.write(result_df)
+    
+main()