Timeline
2020/03/12
2020/06/12
2020/06/26
Competition start: 2020/03/12 00:00:00
Competition closes on: 2020/06/12 00:00:00
Final Submission Limit: 2020/06/26 00:00:00
This competition does not have a "Late Submission" option.
Description
- a decrease in efficiency
- an increase in capital costs, the reassignment of flight crews and aircraft
- an additional crew expense
Consequently, on balance, an airline's history of flight delays can have a negative effect on passenger demand.
This competition is intended to predict the estimated length of flight delays for each
This solution proposes to build a prediction model of flight delay using automatic learning techniques. The accurate prediction of flight delays will help all actors in the air travel ecosystem to establish effective action plans to reduce the impact of delays and avoid loss of time, capital and resources.
Evaluation
Then the csv file to be sent should look like this:
id target test_id_0 2470 test_id_1 30
This means that the flight on the date (mapping to test_id_1) for the flight number (mapping to test_id_1) will be delayed by 30 minutes.
Rules
Since this is a learning challenge (the competitor will earn points, not cash), other than the rules in the DataSource Terms of Use, no other particular rules apply.
Maximum 10 solutions submitted per day.
Please note that there is no public/private leaderboard split for this challenge.
Note: We reserve the right to modify these rules at any time as needed.