10,000pts
Timeline
Begin
2021/01/17
2021/01/17
Finish
2021/03/31
2021/03/31
Complete
2021/04/07
2021/04/07
Competition start: 2021/01/17 00:00:00
Competition closes on: 2021/03/31 00:00:00
Final Submission Limit: 2021/04/07 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.
Once the whole process is completed, you will still be able to submit models as "Late Submission" as a learning experience, since, since the competition is officially over, those models will not be eligible to win prizes.
Once the whole process is completed, you will still be able to submit models as "Late Submission" as a learning experience, since, since the competition is officially over, those models will not be eligible to win prizes.
Description
In this competition, we will analyze the activity of users who vist a service/product offered online through a website. The objective is to predict which visitors will decide to buy according to the characteristics and interactions they exhibit on the site.
In this special case, we are working with a classification/clustering problem. Of the 12.330 sessions on the website, 84.58% did not decide to make a purchase, which equals 10.422 and the rest ended up buying (1908)
In this special case, we are working with a classification/clustering problem. Of the 12.330 sessions on the website, 84.58% did not decide to make a purchase, which equals 10.422 and the rest ended up buying (1908)
Evaluation
The Evaluation of the competition will be done by performing the F1 Score ("Macro") metric.
First we define the F1 score
F1 = 2 * (precision * recall) / (precision + recall)
The Macro F1 score will be the average of the F1 score of each class as well:
defined as the average of the F1 scores of the classes/labels. This is equal to
F1_macro = F1_clase0 + F1_clase1 / 2
In these links you can find more information about the F1 score:
Note: we automatically perform these evaluations against a validation dataset of ours, but you should take these metrics as a reference for your modeling tests.
Rules
Competition Rules
- The code should not be shared privately. Any code that is shared, must be available to all participants of the competition through the platform
- The solution should use only publicly available open source libraries
- If two solutions get identical scores in the ranking table, the tie-breaker will be the date and time of the submission (the first solution submitted will win).
- We reserve the right to request any user's code at any time during a challenge. You will have 48 hours to submit your code following the code review rules.
- We reserve the right to update these rules at any time.
- Your solution must not infringe the rights of any third party and you must be legally authorized to assign ownership of all copyrights in and to the winning solution code to DataSource.ai.
- Competitors may register and submit solutions as individuals (not as teams, at least for now).
- As this is a learning competition, apart from the rules in the DataSource.ai Terms of Use, no other particular rules apply.
- Maximum 10 solutions submitted per day.
At the end of the competition and if you are in the top 20, you must submit the complete model in .ipynb (Jupyter Notebook) format - no other formats will be accepted. You will have 48 hours after the end of the competition to send it to [email protected] - This model will serve us to get the real final evaluations, so the Leaderboard could change when the final private evaluation is shown.
