Hi Dears,
The goal of the data challenge is to propose you to resolve a use case in data analysis, which is usually taken from real scientific projects and real data (in a simplified form). You will be given with some ecological data and a goal (challenge). You are then free to use any approach and technique to succeed. Depending on the question, sometimes it would be more appropriate to use classical statistical methods, sometimes skills in machine learning may be helpful.
This challenge aims to use statistical or machine learning models (e.g. linear models, support vector machines) to predict the protection status of a see station using its species abundancy.
The challenge provides 2 data.frames (data_test and data_train, see below) corresponding to see stations described by their species abundancy. The goal of this challenge is to predict the protection status of the see station.
The challenge is orchestrated by the Codabench platform, secret URL is: https://www.codabench.org/competitions/1809/?secret_key=a503da4b-9940-4f27-9e08-042c39ffe177
A presentation is also available there: https://youtu.be/TCeBoQ7DvwA
We hope you will enjoy the challenge.
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The biodiv0.1 Challenge Team