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I'm looking for a way to perform multiple simultaneous quantile regression.

I read that the quantile crossing phenomenon is a common issue for that type of tasks, and I must avoid it.

So my question is : does Quantile Forest Regression prevent quantile crossing, or not? If not, could you a better suited method?

Thanks in advance!

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Yes, quantiles of QFR never cross.

Accordingly to the paper of Meinshausen, quantile regresion forest works as follows:

fit: just fit an ordinary ransom forest

predict: for an observation $x$, take all the trainging samples that shared leaves with $x$, and return their quantiles.

Because the algoritm always returns "real" quantiles (although maybe of somehow "imaginary" distribution), they are ordered properly for each possible test sample.

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