This project attempts to model and acquire data from SF OpenData - and other sources - to predict the relative risk of fire in San Francisco’s buildings and public spaces.
1) Merge each specific fire incident to EAS
2) Merge all relevant features from tax roll data
3) Create basic transformations/combinations of relevant features (Ex. "land value per square foot")
4) Remove any outliers
5) Aggregate building type into broader categories
1) Merge each specific fire incident to EAS 2) Merge all relevant features from tax roll data 3) Create basic transformations/combinations of relevant features (Ex. "land value per square foot") 4) Remove any outliers 5) Aggregate building type into broader categories