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Property Valuation — Lagos, Nigeria
Business question
Can we predict listing prices for Lagos residential properties accurately enough to:
- Help buyers spot under-priced or over-priced listings
- Help estate agents anchor pricing recommendations
- Inform mortgage / valuation models for Nigerian lenders
Data
Run python download_data.py.
EDA targets
- Price distribution by neighborhood (Ikoyi, Lekki, VI command premium; outskirts cheaper)
- Bedroom count and property type extracted from
Property_name
- Land vs. Apartment vs. House vs. Duplex price differentials
Modeling
| Family |
Model |
| Linear regression |
OLS on log-price with neighborhood + property-type + bedrooms |
| GBM |
LightGBM / GradientBoostingRegressor with one-hot neighborhood + parsed features |
Validation
- 80/20 random split; metrics: R², MAE on log-price, MAPE
- Compare OLS vs. GBM head-to-head
Deployment
- API
POST /property-valuation returning price estimate + 80% interval
- Estate-agent dashboard with neighborhood-level distribution overlays
Business outcome
- Estate agents and buyers anchor pricing on a model rather than vibes
- Mortgage lenders get an explainable valuation reference
- Same pipeline trivially extends to Abuja, Ibadan, Port Harcourt with neighborhood-tagged data