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) Subset data to potentially useful features
2) Detect and remove outliers
4) Collapse data at EAS level
5) Create any potentially relevant features
6) Any other data cleaning and standardization operations
7) Output as .csv (indexed at EAS)
sewardlee337
commented
6 years ago
1) Subset data to potentially useful features 2) Detect and remove outliers 4) Collapse data at EAS level 5) Create any potentially relevant features 6) Any other data cleaning and standardization operations 7) Output as .csv (indexed at EAS)