🛒 Big Mart Sales Predictor
Predict outlet-level item sales using a trained Random Forest model
₹1,098
CV RMSE
0.586
CV R²
RF + Blend
Best Model
8,523
Training Samples
16 Features
After Engineering
📦 Item Details
Item Category
Food (FD)
Drinks (DR)
Non-Consumable (NC)
Item Type
Fruits and Vegetables
Snack Foods
Household
Frozen Foods
Dairy
Canned
Baking Goods
Health and Hygiene
Soft Drinks
Meat
Breads
Hard Drinks
Others
Starchy Foods
Breakfast
Seafood
Item Fat Content
Low Fat
Regular
Non-Consumable
Item Weight (kg)
12.0
Item MRP (₹)
130
Item Visibility
0.060
🏪 Outlet Details
Outlet Type
Supermarket Type1
Supermarket Type2
Supermarket Type3
Grocery Store
Outlet Size
Small
Medium
High
Outlet Location Tier
Tier 1
Tier 2
Tier 3
Outlet Establishment Year
1999
🔮 Predict Sales
—
Predicted Annual Item-Outlet Sales
📊 Model Benchmark (5-fold CV)
Model
RMSE
R²
Ridge (baseline)
₹1,203
0.502
XGBoost
₹1,143
0.551
LightGBM
₹1,147
0.548
Random Forest
₹1,097
0.586
Blend (RF+XGB+LGB) ✅
₹1,098
0.586
Best