How the Open-Source Valuation Algorithm Works
Commercial AVMs (Zillow Zestimate, Redfin Estimate) keep their spatial weighting and feature importance proprietary. This open-source architecture unifies OpenStreetMap geometric layers, Census tract priors, and spatial decay kernels into a reproducible estimator you can run anywhere.
1. Spatial Gaussian Distance Kernel
Comparable sale prices are weighted using Gaussian spatial decay:
w_i = exp(-(d_i / h)²),
where d_i is the geodesic distance to comp i and h is the user-tunable kernel bandwidth. Close sales dominate the base valuation.
2. OSM Hedonic Feature Extraction
Querying local OpenStreetMap nodes within 1.0 km delivers live proximity counts for public schools, parks, transit nodes, and retail. These amenities provide positive marginal adjustments calibrated from hedonic coefficient benchmarks.
3. Hedonic Attribute Equalization
Delta adjustments equalize differences in square footage, bathroom counts, and construction age:
Adj = Îsqft à P_sqft + Îbeds à P_bed + Îbaths à P_bath