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sales-forecast-model
Abhik19/sales-forecast-model
sales-forecast-model is a machine learning model from Abhik19. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for sklearn. The card lists the license as mit.
This model predicts ProductStoreSalesTotal (revenue) based on product and store attributes.
Access
Public
Updated Jan 19, 2026
Repo size
37.4 MB
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0
Public
Repo makeup
Click a slice to open those files.
.joblib658 KB · 90%
At a glance
- Library
- sklearn
- License
- mit
- Access
- Public
- Created
- Jan 19, 2026
- Updated
- Jan 19, 2026
- SHA
- fa339a10
Model card
From the Hugging Face model README
Sales Forecast Model
Model Description
This model predicts Product_Store_Sales_Total (revenue) based on product and store attributes.
Best Model: Random Forest
Performance Metrics
| Metric | Train | Test |
|---|---|---|
| R² | 0.9714 | 0.9312 |
| RMSE | 179.95 | 280.16 |
| MAE | 65.18 | 107.08 |
Features Used
- Product_Weight
- Product_Allocated_Area
- Product_MRP
- Store_Age
- Product_Sugar_Content_Encoded
- Product_Type_Encoded
- Store_Size_Encoded
- Store_Location_City_Type_Encoded
- Store_Type_Encoded
Usage
from huggingface_hub import hf_hub_download
import joblib
# Download model
model_path = hf_hub_download(repo_id="Abhik19/sales-forecast-model", filename="best_model.joblib")
model = joblib.load(model_path)
# Make predictions
predictions = model.predict(X)
Business Context
Accurate sales forecasting helps:
- Plan sales operations by region
- Optimize supply chain procurement
- Reduce sales pipeline risks
- Establish benchmarks for trend analysis
- Library
- sklearn
- License
- mit
- Created
- Jan 19, 2026
- Updated
- Jan 19, 2026