In this project, we aim to infer the quality of Project Sidewalk users based on their interactions with our system--both low-level interactions like mouse clicks and moves--as well as higher-level, more application related interactions (amount of panning on a street view image, etc.). More details are in our Dropbox folder ProjectSidewalk_PredictingUserQuality

Additional files you will need for the classifier (sidewalk-user-quality-analysis-neil.ipynb):

• users_one_mission.csv: CSV of quality information for users with at least one mission
• sidewalk-seattle-label_point.csv: Information about labels in Seattle
• ml-label-correctness-one-mission.csv: Label correctness for all the labels of users with at least one mission
• all_users.csv: Features generated from the feature generation notebook

If you want to be able to run the classifier from start to finish, use sidewalk-classification-notebook.ipynb.