Covid-19 Latam Prediction
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Covid-19 Latam Prediction

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Description

The essential basis of this competence is to be able to predict the number of people who have been affected (confirmed cases) or unfortunately decl...

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
  • gustavo adolfo parra cerquera
  • Ricardo Rupallan
  • Sidereus
  • Pablo Andrés Leandro Jiménez
  • manuel saponaro
  • David
  • Wilmer Romero Ampuero
132 Competitors Published at: 04/04/2020
Points
10,000pts
This competition is finished
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Timeline

Begin
2020/04/08
Finish
2020/05/31
Complete
2020/06/14

Competition start: 2020/04/08 00:00:00
Competition closes on: 2020/05/31 00:00:00
Final Submission Limit: 2020/06/14 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

The essential basis of this competence is to be able to predict the number of people who have been affected (confirmed cases) or unfortunately declared dead by the COVID virus19 , in Latin America. If you can identify factors in your analysis that may affect the rate of transmission of COVID-19, you can share them.

Presentation file

We understand that this is a serious situation, and in no way do we want to trivialize the human impact this crisis is causing by predicting deaths. Our goal is to provide better methods of estimation that can help medical and government institutions prepare and adjust as pandemics develop.

Time Line
  • 04/08/2020 - Launch of the competition
  • 08/04/2020 - 31//05/2020 - You work the model and test it against test.csv, we update it weekly with the new data from train.csv that we will launch. We are publishing a public table of positions in that period of time.
  • 31//05/2020 - Final presentation file deadline.
  • 06/01/2020 - 06/30/2020 - Evaluation period.
  • 30/06/2020 we show the private position table

The initial data set for the model training will be from February 26 to April 08, 2020.

This dataset will be updated weekly until May 31st. 


Evaluation

The metric for the evaluation of results will be the Root Mean Squared Logarithmic Error (RMSLE):

where:

n is the total number of observations 
pi is the prediction
ai is the current value  

The final score will be the average of the result of the RMSLE metric applied on the 2 columns (ConfirmedCases, Fatalities).

The results presentation file (Submission.csv) must have the following format

ForecastId,ConfirmedCases,Fatalities
1,10,0
2,10,0
3,10,0
etc.

For each ForecastID of the test set, the sum of the ConfirmedCases and Fatalities variables must be predicted, in the date range of the test.csv


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.

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

Points: 10000pts


Train train.csv - Training information dated Mar 18, 2020.
Test test.csv - Dates to predict, there is an overlap of one week
Submission submission.csv - a presentation of the sample in the correct format; again, predictions should be cumulative

  1. Forecast the peak of infected countries.
  2. Compare the total number of infected among Latin America.

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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