[scikit-learn] Recurrent States with Decision Tree

[KevNo]

Hello,

Just wondering, how can we setup path dependant input states for Random 
Forest/Decision Tree ?
This is similar to Recurrent Network,
where input Xt=(x0,...,xi,.. yt-1, yt-2) depends on past output states Yt.


If we could put the exact values states Yt, it obviously creates a bias 
in the training.
So, we should be put some estimate of (Yt)


Is the concept of Recurrent Tree makes sense ?

Thanks for your insight.





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