3 years, 5 months ago
Second Semester Project for Machine Learning 2020/2021 Course
This is the second semester project for students enrolled in the Machine Learning 2020/2021 course (1000-2N09SUS) at the Faculty of Mathematics, Informatics and Mechanics of the University of Warsaw.
The goal of this competition is to create an efficient forecasting model for predicting sales of products offered by the FitFood company at one of their FitBoxy locations in Poland (FitBoxy - Inteligentna lodówka).
More detailed competition rules are given in Terms and Conditions.
The description of the data and evaluation metric is in the Task description section.
The submission system opens on Tuesday, May 18. The deadline for sending the solutions and reports is Friday, June 11, 23:59 GMT.
Provided data describe a short-term sales history of products offered in FitBoxy vending machines at various points of sales (PoS). The prediction targets from the SUS_project_training_targets.txt file, correspond to future 7-day sales of a given product at a particular location.
The data is provided in a tabular format, with each row corresponding to a different instance.
The data tables are provided as two CSV files with the ';' separator sign. They can be downloaded after the registration for the challenge. Both files (training and test sets) have exactly the same format. The target values for the training data is provided as a separate file.
The evaluation metric will be R^2. During the challenge, your solutions will be evaluated on a small fraction of the test set (5000 instances), and your best preliminary score will be displayed on the public Leaderboard.
The submission format: the solutions need to be submitted as text files with predictions. The file should have exactly the same number of rows as the test data table (i.e. 70000 rows). In each row, it should contain exactly one real number expressing the predicted sales in the following 7 days.
The competition is sponsored by QED Software
Rank | Team Name | Is Report | Preliminary Score | Final Score | Submissions | |
---|---|---|---|---|---|---|
1 | Michał Kardaś |
True | True | 0.4743 | 0.480300 | 10 |
2 | Nie_wiem_jak_sie_nazwac |
True | True | 0.4319 | 0.449100 | 2 |
3 | Krzysztof Witczyński |
True | True | 0.4469 | 0.447100 | 31 |
4 | Kajetan Husiatyński |
True | True | 0.4248 | 0.434800 | 18 |
5 | aaaa11 |
True | True | 0.4361 | 0.433100 | 24 |
6 | TM |
True | True | 0.4381 | 0.432000 | 39 |
7 | MateuszBiesiadowski |
True | True | 0.4324 | 0.430500 | 11 |
8 | -_- |
True | True | 0.4236 | 0.424400 | 8 |
9 | Marcin Abramowicz |
True | True | 0.4137 | 0.423100 | 14 |
10 | Tomasz Cheda |
True | True | 0.4080 | 0.416900 | 6 |
11 | GK |
True | True | 0.4185 | 0.414200 | 8 |
12 | jc406120 |
True | True | 0.4016 | 0.411500 | 3 |
13 | Tomasz Patyna |
True | True | 0.4097 | 0.409900 | 10 |
14 | MarcinKurowski |
True | True | 0.3930 | 0.406800 | 17 |
15 | Rafał Czarnecki |
True | True | 0.3752 | 0.391600 | 6 |
16 | 2137 |
True | True | 0.3579 | 0.375000 | 7 |
17 | Michał Niedziółka |
True | True | 0.3487 | 0.350300 | 6 |
18 | mg359198 |
True | True | 0.3829 | 0.337600 | 7 |
19 | tdtd |
True | True | 0.3215 | 0.331300 | 3 |
20 | Jan Jurkowski |
True | True | 0.3592 | 0.318600 | 5 |
21 | mo406269 |
True | True | 0.3091 | 0.312600 | 10 |
22 | MagdaMalinowska |
True | True | 0.2721 | 0.272800 | 15 |
23 | sb406106 |
True | True | -0.5238 | -0.524200 | 1 |
24 | -_- |
True | True | 0.4236 | -1.443000 | 8 |