Upload project_app.py

project_app.py

@@ -0,0 +1,35 @@
+   
+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()