japa-swadia / r_sf-crime-analysis Goto Github PK

Worked to apply data science techniques like classification, regression, clustering and association mining on San Francisco city's crime data which can aid SFPD Crime Analysis Unit in curbing crime incidents; by creating a model in R that predicts type of crime based on location and time, estimates annual number of crime incidents in an area, and discovers associations between various crime types to determine 'top' crimes by area and 'top' days of the week for such occurrences.