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Welcome to our fifteenth Conundrum. This week we have a little Modelling puzzle for you to get stuck into!
Attached is a dataset with details of individual athletes competing in specific Olympic events.
Of course they are all hunting for that elusive Gold medal - but what gets them there? Can you build a model to expose the most important factors in getting the Gold?
Included are features like high, weight, year of the games and more - what do you think will be the most significant?
@gerryleonugroho Great question! Looking over at the other conundrum, for FIFA, I think you might be on to something. Indeed, "wage" and "medal" could equate, and "skills" and "factors" could also equate. So, it might be a similar type of conundrum.
My idea for this one is that I might be trying to predict "gold medal" vs "not gold medal" but first, how would I group the data?
Your solution for grouping/clustering the player's skillsets in the FIFA conundrum gives me some ideas about 'interactive clustering' that I would not have thought of before. Good luck and I can't wait to see what you come up with!
Hey @gerryleonugroho - somewhat similar, but one big difference here is that there is a much more concrete condition that determines success: the gold! So it's much less about creating a subjective value proposition - and more about trying to determine importance in a more empirical way.