Create app.py

app.py

@@ -0,0 +1,20 @@
+import numpy as np
+import pickle
+import warnings
+import streamlit as st
+
+warnings.simplefilter("ignore", UserWarning)
+
+MODEL = pickle.load(open('IF_model_anomaly.pkl','rb'))
+
+st.title("Retail Anomaly")
+def prediction(sales,model):
+    sales = np.float64(sales)
+    pred = model.predict(sales.reshape(-1,1))[0]
+    if pred == -1:
+        return "Outlier"
+    else:
+        return "Not outlier"
+
+sales = st.number_input("Enter the Sales Value")
+st.header(prediction(sales,MODEL))