User:KWeathington

Mentor: Dr. Shion Guha
Lab Github: https://github.com/marquettecomputationalsocialscience
Personal Github:https://github.com/KatyWeathington

Week One

• Orientation

• Data discussion meeting and updating new team members on previous work and lab goals

• Background reading on various spatial clustering algorithms and use of data science concepts in police departments

Week Two

• Compiled a preliminary list of clustering algorithms sorted into family, with a note of potential sources of biases and a summary of the steps

• Demonstrated a variety of clustering algorithms on random data

• Explored Kernel Density Estimates

Week Three

• Expanding a dictionary for sanitizing address data

• RCR Training

• Made a poster for upcoming Northwestern Mutual event

• Opened API keys

Week Four

• Added basemap to DBScan visualization

• Created several DBScan clustering models of crime in Milwaukee

• Presented research at Northwestern Mutual technology showcase at announcement of the Data Science Institute

Week Five

• Reporting halfway progress

• More DBScan and nearest neighbors based calculation of epsilon

• Began developing theory and equation for a "wastage index"

Week Six

• Implemented a K Nearest Neighbors plot to help identify optimal eps given a minPT value on certain subsections of the data

• Added hulls around individual clusters to make more user friendly

Week Seven

• Further background reading

• Cultivating literature for paper

Week Eight

• Began write up about DBScan findings

• Made poster for end of summer poster session

Week Nine

• Continued final paper writing

Week Ten

• Poster session

• Final presentations

• Finished final write-up