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app.py

@@ -2,7 +2,7 @@ import streamlit as st
 import pandas as pd
 import joblib
 
-# Load the trained model
+# Loading the trained model
 model = joblib.load("best_random_forest_model.pkl")
 
 st.set_page_config(page_title="SuperKart Sales Prediction", layout="centered")
@@ -15,11 +15,9 @@ st.subheader("📦 Product Details")
 Product_Weight = st.number_input("Product Weight (kg)", min_value=0.0, value=10.0, step=0.1)
 Product_Sugar_Content = st.selectbox("Product Sugar Content", ["Low Sugar", "Regular", "No Sugar"])
 Product_Allocated_Area = st.number_input("Product Allocated Area (sq. m.)", min_value=0.0, value=1.0, step=0.1)
-Product_Type = st.selectbox("Product Type", [
-    "Dairy", "Soft Drinks", "Meat", "Fruits", "Snack Foods", "Household",
-    "Baking Goods", "Health and Hygiene", "Frozen Foods", "Hard Drinks",
-    "Canned", "Breads", "Starchy Foods", "Breakfast", "Seafood", "Others"
-])
+Product_Type = st.selectbox("Product Type", ['Frozen Foods' 'Dairy' 'Canned' 'Baking Goods' 'Health and Hygiene'
+ 'Snack Foods' 'Meat' 'Household' 'Hard Drinks' 'Fruits and Vegetables'
+ 'Breads' 'Soft Drinks' 'Breakfast' 'Others' 'Starchy Foods' 'Seafood'])
 Product_MRP = st.number_input("Product MRP (₹)", min_value=0.0, value=120.0, step=0.5)
 
 # --- Store Inputs ---

best_random_forest_model.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:02a80442a85c24b2707ae4d590ab4d32ec9de47ac9f7da57d4278eb9c846b672
-size 34699082
+oid sha256:90adfd92d44772800d09470b4cf083e26608da16363ca4092a35fb1bf30e84d2
+size 63804778