Decision tree – a bit of Data Mining

As this blog is slowly growing up, I still have a chance to explain how relatively simple approaches can solve complex problems. Please be invited to read a bit of explanation on how to make decisions based on a non-linear dataset.

The idea for this article came up in parallel with the article describing the application which supports the process of buying football players in FIFA 2016 (link here: Lewandowski, Messi, Ronaldo, Mbappé – who’s worth buying in FIFA 2016). The aim was to split the application and explanation of results interpretation from a detailed description of what are the rules behind it.

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Lewandowski, Messi, Ronaldo, Mbappé – who’s worth buying in FIFA 2016

This article is about a piece of code about checking which FIFA footballers you should invest in FIFA 2016. Even if you’re more into doing sports outside than spending time while playing sport video games, it might be worth checking.

It’s more than evident that having a stronger team gives you by default dominance on a pitch. But how to do that having limited funds in a video game? The answer might be shocking, but let’s predict who’s going to be worth more in upcoming seasons…

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