Flight Delay Prediction Competition
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Flight Delay Prediction Competition

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Description

This challenge was designed because flight delays not only irritate air passengers and disrupt their schedules, but also cause them:a decrease in e...

Prizes
These will be the awards once the competition is over:1st Place: 10.000 pts 2nd Place: 9.000 pts 3rd Place: 8.000 pts 4th Place: 7.000 pts 5th Plac...
Competitors
  • Armando
  • Clynton Tomacheski
  • Diego Palma
  • Meiker Lazo Colonio
  • Hans Hidalgo Alta
  • Guillermo Ruiz
  • Diego Alexander Rueda Plata
101 Competitors Published at: 03/12/2020
Total Prize
$0
This competition is finished
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Timeline

Begin
2020/03/12
Finish
2020/06/12
Complete
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 has a total duration of 3 months, within which you will be able to make your submissions and obtain results automatically. Once the first part of the competition is over, you will have one week to choose your best model and submit it to be graded and considered for cash or points prizes. 

This competition does not have a "Late Submission" option.


Description

This challenge was designed because flight delays not only irritate air passengers and disrupt their schedules, but also cause them:

  • 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

The metric used for this challenge is the Root Mean Squared Logarithmic Error (RMSLE).

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

Competitors can register and submit solutions as individuals not as teams (at least for now).

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.


These will be the awards once the competition is over:

1st Place: 10.000 pts 
2nd Place: 9.000 pts 
3rd Place: 8.000 pts 
4th Place: 7.000 pts 
5th Place: 6.000 pts 
6th Place: 5.000 pts 
7th Place: 4.000 pts 
8th Place: 3.000 pts 
9th Place: 2.000 pts 
10th Place: 1.000 pts
Points: 10000pts

Total Prize: $0


Files available for download

Train.csv - the training file
Test.csv - the test file
SampleSubmission.csv - is an example of what your presentation file should look like. The order of the rows does not matter, but the names of the IDs must be correct. The "target" column is your prediction.

Variable Definitions
  • ID - id
  • DATOP - Date of flight
  • FLTID - Flight number
  • DEPSTN - Departure point
  • ARRSTN - Arrival point
  • STD - Scheduled Time departure
  • STA - Scheduled Time arrival
  • STATUS - Flight status
  • AC - Aircraft Code
  • target - Delay Time

For this competition stage, you need to send your submission file with this details:

# of columns:
Column names: ,
# of rows:

This competition is finished


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