Number of air passengers prediction, DSSP4/5 2016
The data set was donated to us by an unnamed company handling flight ticket reservations. The data is thin, it contains
  • the date of departure
  • the departure airport
  • the arrival airport
  • the mean and standard deviation of the number of weeks of the reservations made before the departure date
  • a field called log_PAX which is related to the number of passengers (the actual number were changed for privacy reasons)
The goal is to predict the log_PAX column. The prediction quality is measured by RMSE. The data is obviously limited, but since data and location informations are available, it can be joined to external data sets. The challenge in this RAMP is to find good data that can be correlated to flight traffic.
  • Submissions will open at (UTC) 2000-01-01 00:00:00
  • When you submit, your submission is sent to be trained automatically. The jobs may wait some time in a queue before being run so be patient.
  • Pending (untrained) and failing submissions can be resubmitted under the same name at an arbitrary frequency.
  • Once your submission is trained, it cannot be deleted or replaced.
  • After each succesfully trained submission, you have to wait 900s to resubmit.
  • The leaderboard is in "hidden" mode until (UTC) 2000-01-01 00:00:00 which means that all scores are visible, but the links pointing to the code of the participants are hidden. After (UTC) 2000-01-01 00:00:00, all submitted codes are public. You will be encouraged to look at and reuse each other's code.